From 66c7e3ef975ff1066ab859106b2fb8d2bd36f71b Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 10:15:19 -0500 Subject: [PATCH 001/162] add correct_mask simplest --- plantcv/annotate/classes.py | 89 ++++++++++++++++++++++++++++++++++++- 1 file changed, 87 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 455701e..7c1b356 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -1,13 +1,35 @@ # Class helpers # Imports +import os import cv2 import json +import numpy as np from math import floor import matplotlib.pyplot as plt from plantcv.plantcv.annotate.points import _find_closest_pt -from plantcv.plantcv import warn - +from plantcv.plantcv import warn, params, _debug + + +def _remove_points(autolist, confirmedlist): + """Function to remove points if interactively removed by user + Inputs: + autolist = total list of coordinates, automatically generated + from the contents of coords attribute + confirmedlist = coordinates of 'auto' detected points (e.g. coordinate + output of pcv.filters.eccentricity) + Returns: + removecoor = list of coordinates (of objects to remove from the binary mask) + :param autolist: list + :param confirmedlist: list + :return removecoor: list + """ + # internal function to remove to remove points specified by a user + removecoor = [] + for element in autolist: + if element not in confirmedlist: + removecoor.append(element) + return removecoor class Points: """Point annotation/collection class to use in Jupyter notebooks. It allows the user to @@ -158,3 +180,66 @@ class label, by default "default" else: for (x, y) in self.coords[self.label]: self.ax.plot(x, y, marker='x', c=self.color) + +def correct_mask(self, bin_img, bin_img_recover, coords): + """View coordinates for a specific class label. + + Parameters + ---------- + bin_img : numpy.ndarray + binary image, filtered mask image with selected objects + bin_img_recover : numpy.ndarray + binary image, unclean mask image with all potential objects + coords : list + coordinates of 'auto' detected points (coordinate output of annotate.get_centroids) + + Returns + ---------- + completed_mask : numpy.ndarray + corrected binary mask with recovered and removed objects + """ + from plantcv.plantcv.floodfill import floodfill + + debug = params.debug + params.debug = None + + labelnames = list(self.count) + + completed_mask = np.copy(bin_img) + + totalcoor = [] + unrecovered_ids = [] + + for names in labelnames: + for i, (x, y) in enumerate(self.coords[names]): + x = int(x) + y = int(y) + totalcoor.append((y, x)) + + removecoor = _remove_points(coords, totalcoor) + removecoor = list(map(lambda sub: (sub[1], sub[0]), removecoor)) + completed_mask = floodfill(completed_mask, removecoor, 0) + + # points in class used for recovering and labeling + all_coords = [] + for names in labelnames: + for i, (x, y) in enumerate(self.coords[names]): + x = int(x) + y = int(y) + # corrected coordinates + self.coords[names][i] = (x, y) + all_coords.append((x,y)) + total_mask_minus_objs = floodfill(bin_img_recover, all_coords, 0) + recovered_objs = bin_img_recover - total_mask_minus_objs + completed_mask = completed_mask + recovered_objs + + completed_mask1 = 1*((completed_mask + 1*(completed_mask == 255)) != 0).astype(np.uint8) + + params.debug = debug + + _debug(visual=completed_mask1, + filename=os.path.join(params.debug_outdir, + f"{params.device}_annotation-corrected.png")) + + return completed_mask1 + From 0eb7698470d78402c897aabb0d49656e36bf72b7 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 10:30:14 -0500 Subject: [PATCH 002/162] Split up "coords" attribute into two classes, normal vs unrecovered --- plantcv/annotate/classes.py | 31 +++++++++++++++++++++++++------ 1 file changed, 25 insertions(+), 6 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 7c1b356..28417ee 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -221,17 +221,36 @@ def correct_mask(self, bin_img, bin_img_recover, coords): completed_mask = floodfill(completed_mask, removecoor, 0) # points in class used for recovering and labeling - all_coords = [] for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): x = int(x) y = int(y) # corrected coordinates - self.coords[names][i] = (x, y) - all_coords.append((x,y)) - total_mask_minus_objs = floodfill(bin_img_recover, all_coords, 0) - recovered_objs = bin_img_recover - total_mask_minus_objs - completed_mask = completed_mask + recovered_objs + if completed_mask[y, x] == 0 and bin_img_recover[y,x] > 0: + print(f"Recovering object at coordinates: x = {x}, y = {y}") + total_mask_minus_objs = floodfill(bin_img_recover, [(y,x)], 0) + recovered_objs = bin_img_recover - total_mask_minus_objs + completed_mask = completed_mask + recovered_objs + elif completed_mask[y, x] == 0 and bin_img_recover[y,x] == 0: + print(f"Un-Recoverable object at coordinates: x = {x}, y = {y}") + unrecovered_ids.append(i) + + # Split up "coords" attribute into two classes + unrec_points = [] + for id in unrecovered_ids: + (x, y) = self.coords[names][id] + unrec_points.append((x, y)) + new_name = str(names) + "_unrecovered" + # Pull out unrecovered coords into new class + self.coords[new_name] = unrec_points + # Overwrite class with only coords that have corresponding objects in the completed_mask + new_points = [] + for i, (x, y) in enumerate(self.coords[names]): + if i not in unrecovered_ids: + new_points.append((x, y)) + + self.coords[names] = new_points + completed_mask1 = 1*((completed_mask + 1*(completed_mask == 255)) != 0).astype(np.uint8) From 7978e7500d34baad15bc467ffa2938b12aa9f744 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 10:38:15 -0500 Subject: [PATCH 003/162] indent fix --- plantcv/annotate/classes.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 28417ee..ce94746 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -181,7 +181,7 @@ class label, by default "default" for (x, y) in self.coords[self.label]: self.ax.plot(x, y, marker='x', c=self.color) -def correct_mask(self, bin_img, bin_img_recover, coords): + def correct_mask(self, bin_img, bin_img_recover, coords): """View coordinates for a specific class label. Parameters @@ -257,8 +257,8 @@ def correct_mask(self, bin_img, bin_img_recover, coords): params.debug = debug _debug(visual=completed_mask1, - filename=os.path.join(params.debug_outdir, - f"{params.device}_annotation-corrected.png")) + filename=os.path.join(params.debug_outdir, + f"{params.device}_annotation-corrected.png")) return completed_mask1 From 611a0ffdd5cd76bf60c9904cf49e76b6a3d4f1ce Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 10:41:27 -0500 Subject: [PATCH 004/162] change debug import --- plantcv/annotate/classes.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index ce94746..19eb24c 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -8,7 +8,9 @@ from math import floor import matplotlib.pyplot as plt from plantcv.plantcv.annotate.points import _find_closest_pt -from plantcv.plantcv import warn, params, _debug +from plantcv.plantcv import warn, params +from plantcv.plantcv._debug import _debug + def _remove_points(autolist, confirmedlist): From 018ec54e3e15aa2d19a39f0472b4ed9285cab839 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 10:55:02 -0500 Subject: [PATCH 005/162] swap x.y for floodfill call --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 19eb24c..9cb7789 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -230,7 +230,7 @@ def correct_mask(self, bin_img, bin_img_recover, coords): # corrected coordinates if completed_mask[y, x] == 0 and bin_img_recover[y,x] > 0: print(f"Recovering object at coordinates: x = {x}, y = {y}") - total_mask_minus_objs = floodfill(bin_img_recover, [(y,x)], 0) + total_mask_minus_objs = floodfill(bin_img_recover, [(x, y)], 0) recovered_objs = bin_img_recover - total_mask_minus_objs completed_mask = completed_mask + recovered_objs elif completed_mask[y, x] == 0 and bin_img_recover[y,x] == 0: From 15a7d274246b13b6556571ff49b618039ca41e05 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 11:48:36 -0500 Subject: [PATCH 006/162] adding test data --- tests/conftest.py | 6 ++++++ tests/testdata/pollen_all_mask.png | Bin 0 -> 5856 bytes tests/testdata/pollen_detectdisc_mask.png | Bin 0 -> 2890 bytes 3 files changed, 6 insertions(+) create mode 100644 tests/testdata/pollen_all_mask.png create mode 100644 tests/testdata/pollen_detectdisc_mask.png diff --git a/tests/conftest.py b/tests/conftest.py index 4023056..1796edb 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -24,6 +24,12 @@ def __init__(self): self.kmeans_seed_gray_img = os.path.join(self.datadir, "silphium_seed_labeled_example.png") # Small Hyperspectral image self.envi_sample_data = os.path.join(self.datadir, "corn-kernel-hyperspectral.raw") + # Binary mask including all pollen grainss + self.pollen_all = os.path.join(self.datadir, 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007/162] Update conftest.py --- tests/conftest.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/tests/conftest.py b/tests/conftest.py index 1796edb..3cc5ada 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -28,9 +28,6 @@ def __init__(self): self.pollen_all = os.path.join(self.datadir, "pollen_all_mask.png") # Binary mask Eccentricity filtered objects self.pollen_discs = os.path.join(self.datadir, "pollen_detectdisc_mask.png") - # Labeled mask from watershed segmentation - self.pollen_watershed = os.path.join(self.datadir, "pollen_watershed.png") - @pytest.fixture(scope="session") def test_data(): From 2bb3a256d32df443a37223b3d8a08f8046856b96 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 11:49:02 -0500 Subject: [PATCH 008/162] add correct test --- tests/test_annotate_points.py | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index c74769b..5ffbf60 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -2,6 +2,7 @@ import os import cv2 import matplotlib +import numpy as np from plantcv.annotate.classes import Points @@ -157,3 +158,22 @@ def test_points_view_warn(test_data): drawer_rgb.view(label="new", color='r') assert str(drawer_rgb.fig) == "Figure(1200x600)" + + +def test_plantcv_annotate_points_correct(test_data): + """Test for PlantCV.""" + # Create a test tmp directory + # generate fake testing image + allmask = cv2.imread(test_data.pollen_all, -1) + discs = cv2.imread(test_data.pollen_discs, -1) + coor = [(158, 531), (265, 427), (361, 112), (500, 418)] + totalpoints1 = [(158, 531), (361, 112), (500, 418), (269.25303806488864, 385.69839981447126), + (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963), (240.49608073650273, 277.1640769944342), + (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), (423.24190633947126, 364.3625927643785), + (509.5127783246289, 353.2308673469388), (527, 275), (445.50535717435065, 138.94515306122452)] + counter = Points(np.copy(allmask), figsize=(8, 6)) + counter.import_list(totalpoints1, label="total") + + corrected_mask = counter.correct(bin_img=discs, bin_img_recover=allmask, coords=coor) + assert np.count_nonzero(discs) < np.count_nonzero(corrected_mask) + assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) \ No newline at end of file From 06ac93f62aebbe98e8ba8273b39d974cbdbca82b Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 11:50:50 -0500 Subject: [PATCH 009/162] Update test_annotate_points.py --- tests/test_annotate_points.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 5ffbf60..9b0205b 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -160,7 +160,7 @@ def test_points_view_warn(test_data): assert str(drawer_rgb.fig) == "Figure(1200x600)" -def test_plantcv_annotate_points_correct(test_data): +def test_plantcv_annotate_points_correct_mask(test_data): """Test for PlantCV.""" # Create a test tmp directory # generate fake testing image @@ -174,6 +174,6 @@ def test_plantcv_annotate_points_correct(test_data): counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") - corrected_mask = counter.correct(bin_img=discs, bin_img_recover=allmask, coords=coor) + corrected_mask = counter.correct_mask(bin_img=discs, bin_img_recover=allmask, coords=coor) assert np.count_nonzero(discs) < np.count_nonzero(corrected_mask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) \ No newline at end of file From 2c513edba69cd2198a2d85f439f8fcaae870b679 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 13:05:13 -0500 Subject: [PATCH 010/162] deepsource issues --- plantcv/annotate/classes.py | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 9cb7789..f586936 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -12,7 +12,6 @@ from plantcv.plantcv._debug import _debug - def _remove_points(autolist, confirmedlist): """Function to remove points if interactively removed by user Inputs: @@ -33,6 +32,7 @@ def _remove_points(autolist, confirmedlist): removecoor.append(element) return removecoor + class Points: """Point annotation/collection class to use in Jupyter notebooks. It allows the user to interactively click to collect coordinates from an image. Left click collects the point and @@ -228,12 +228,12 @@ def correct_mask(self, bin_img, bin_img_recover, coords): x = int(x) y = int(y) # corrected coordinates - if completed_mask[y, x] == 0 and bin_img_recover[y,x] > 0: + if completed_mask[y, x] == 0 and bin_img_recover[y, x] > 0: print(f"Recovering object at coordinates: x = {x}, y = {y}") total_mask_minus_objs = floodfill(bin_img_recover, [(x, y)], 0) recovered_objs = bin_img_recover - total_mask_minus_objs completed_mask = completed_mask + recovered_objs - elif completed_mask[y, x] == 0 and bin_img_recover[y,x] == 0: + elif completed_mask[y, x] == 0 and bin_img_recover[y, x] == 0: print(f"Un-Recoverable object at coordinates: x = {x}, y = {y}") unrecovered_ids.append(i) @@ -253,14 +253,12 @@ def correct_mask(self, bin_img, bin_img_recover, coords): self.coords[names] = new_points - completed_mask1 = 1*((completed_mask + 1*(completed_mask == 255)) != 0).astype(np.uint8) params.debug = debug _debug(visual=completed_mask1, - filename=os.path.join(params.debug_outdir, - f"{params.device}_annotation-corrected.png")) + filename=os.path.join(params.debug_outdir, + f"{params.device}_annotation-corrected.png")) return completed_mask1 - From d8d2f548e8e8596d1d2bc8ffaf705d02ec699cc0 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 13:17:17 -0500 Subject: [PATCH 011/162] only add "unrecovered" class to annotations when there are some for that class --- plantcv/annotate/classes.py | 25 +++++++++++++------------ 1 file changed, 13 insertions(+), 12 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index f586936..ee400f0 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -238,18 +238,19 @@ def correct_mask(self, bin_img, bin_img_recover, coords): unrecovered_ids.append(i) # Split up "coords" attribute into two classes - unrec_points = [] - for id in unrecovered_ids: - (x, y) = self.coords[names][id] - unrec_points.append((x, y)) - new_name = str(names) + "_unrecovered" - # Pull out unrecovered coords into new class - self.coords[new_name] = unrec_points - # Overwrite class with only coords that have corresponding objects in the completed_mask - new_points = [] - for i, (x, y) in enumerate(self.coords[names]): - if i not in unrecovered_ids: - new_points.append((x, y)) + if len(unrecovered_ids) > 0: + unrec_points = [] + for id in unrecovered_ids: + (x, y) = self.coords[names][id] + unrec_points.append((x, y)) + new_name = str(names) + "_unrecovered" + # Pull out unrecovered coords into new class + self.coords[new_name] = unrec_points + # Overwrite class with only coords that have corresponding objects in the completed_mask + new_points = [] + for i, (x, y) in enumerate(self.coords[names]): + if i not in unrecovered_ids: + new_points.append((x, y)) self.coords[names] = new_points From 57bb76206f615c596c6a04db4d800dfd6ad1e8b4 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 13:21:32 -0500 Subject: [PATCH 012/162] another indent and update comments --- plantcv/annotate/classes.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index ee400f0..8ddff30 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -244,15 +244,14 @@ def correct_mask(self, bin_img, bin_img_recover, coords): (x, y) = self.coords[names][id] unrec_points.append((x, y)) new_name = str(names) + "_unrecovered" - # Pull out unrecovered coords into new class + # Put unrecovered coords into new class self.coords[new_name] = unrec_points - # Overwrite class with only coords that have corresponding objects in the completed_mask + # Overwrite attribute, only coords that have corresponding objects in the completed_mask new_points = [] for i, (x, y) in enumerate(self.coords[names]): if i not in unrecovered_ids: new_points.append((x, y)) - - self.coords[names] = new_points + self.coords[names] = new_points completed_mask1 = 1*((completed_mask + 1*(completed_mask == 255)) != 0).astype(np.uint8) From 531be5abf11f7ea5632bef803a161125b8ef7d4a Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 13:32:40 -0500 Subject: [PATCH 013/162] update print statements --- plantcv/annotate/classes.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 8ddff30..5aefe21 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -219,6 +219,7 @@ def correct_mask(self, bin_img, bin_img_recover, coords): totalcoor.append((y, x)) removecoor = _remove_points(coords, totalcoor) + print(f"Removing objects at coordinates: {removecoor}") removecoor = list(map(lambda sub: (sub[1], sub[0]), removecoor)) completed_mask = floodfill(completed_mask, removecoor, 0) @@ -229,12 +230,12 @@ def correct_mask(self, bin_img, bin_img_recover, coords): y = int(y) # corrected coordinates if completed_mask[y, x] == 0 and bin_img_recover[y, x] > 0: - print(f"Recovering object at coordinates: x = {x}, y = {y}") + print(f"Recovering object at coordinate: x = {x}, y = {y}") total_mask_minus_objs = floodfill(bin_img_recover, [(x, y)], 0) recovered_objs = bin_img_recover - total_mask_minus_objs completed_mask = completed_mask + recovered_objs elif completed_mask[y, x] == 0 and bin_img_recover[y, x] == 0: - print(f"Un-Recoverable object at coordinates: x = {x}, y = {y}") + print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) # Split up "coords" attribute into two classes From a7976b13dd4fc878904e9d354d86e3fee5b9af46 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 15:18:13 -0500 Subject: [PATCH 014/162] update the way objects are removed check against overlap with any annotation rather than just considering pts auto detected somwhere vs kept coordinates after fixing annotations --- plantcv/annotate/classes.py | 23 ++++++++++++++++++----- 1 file changed, 18 insertions(+), 5 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 5aefe21..b624051 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -10,6 +10,7 @@ from plantcv.plantcv.annotate.points import _find_closest_pt from plantcv.plantcv import warn, params from plantcv.plantcv._debug import _debug +from plantcv.plantcv import create_labels, apply_mask def _remove_points(autolist, confirmedlist): @@ -211,17 +212,29 @@ def correct_mask(self, bin_img, bin_img_recover, coords): totalcoor = [] unrecovered_ids = [] + pts_mask = np.zeros(np.shape(bin_img)) for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): x = int(x) y = int(y) totalcoor.append((y, x)) - - removecoor = _remove_points(coords, totalcoor) - print(f"Removing objects at coordinates: {removecoor}") - removecoor = list(map(lambda sub: (sub[1], sub[0]), removecoor)) - completed_mask = floodfill(completed_mask, removecoor, 0) + # Draw pt annotations onto a blank mask + pts_mask = cv2.circle(pts_mask, (x,y), radius=0, color=(255), thickness=-1) + + + # Only removes objects that were auto detected and then removed + labeled_mask, total_obj_num = create_labels(mask=bin_img) + # Objects that overlap with annotations get kept + masked_image = apply_mask(img=labeled_mask, mask=pts_mask, mask_color='black') + keep_object_ids = np.unique(masked_image) + + for i in range(1,total_obj_num): + if i not in keep_object_ids: + # Fill in objects that are not overlapping with an annotation + labeled_mask[np.where(labeled_mask == i)] = 0 + #labeled_mask = np.where(labeled_mask == i, 0, labeled_mask) + completed_mask = np.where(labeled_mask > 0, 255, 0) # points in class used for recovering and labeling for names in labelnames: From 3cddb7c869cbc5227d6f5a9b9c7250cd8648fdd5 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 15:18:53 -0500 Subject: [PATCH 015/162] remove unnecessary param --- plantcv/annotate/classes.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index b624051..a570518 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -184,7 +184,7 @@ class label, by default "default" for (x, y) in self.coords[self.label]: self.ax.plot(x, y, marker='x', c=self.color) - def correct_mask(self, bin_img, bin_img_recover, coords): + def correct_mask(self, bin_img, bin_img_recover): """View coordinates for a specific class label. Parameters @@ -193,8 +193,6 @@ def correct_mask(self, bin_img, bin_img_recover, coords): binary image, filtered mask image with selected objects bin_img_recover : numpy.ndarray binary image, unclean mask image with all potential objects - coords : list - coordinates of 'auto' detected points (coordinate output of annotate.get_centroids) Returns ---------- @@ -222,7 +220,6 @@ def correct_mask(self, bin_img, bin_img_recover, coords): # Draw pt annotations onto a blank mask pts_mask = cv2.circle(pts_mask, (x,y), radius=0, color=(255), thickness=-1) - # Only removes objects that were auto detected and then removed labeled_mask, total_obj_num = create_labels(mask=bin_img) # Objects that overlap with annotations get kept From bdb9607e2110cbcb38bcc1c0d9d9912d98470da3 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 15:20:01 -0500 Subject: [PATCH 016/162] also remove coords from tests --- tests/test_annotate_points.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 9b0205b..f6175cf 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -166,7 +166,6 @@ def test_plantcv_annotate_points_correct_mask(test_data): # generate fake testing image allmask = cv2.imread(test_data.pollen_all, -1) discs = cv2.imread(test_data.pollen_discs, -1) - coor = [(158, 531), (265, 427), (361, 112), (500, 418)] totalpoints1 = [(158, 531), (361, 112), (500, 418), (269.25303806488864, 385.69839981447126), (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963), (240.49608073650273, 277.1640769944342), (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), (423.24190633947126, 364.3625927643785), @@ -174,6 +173,6 @@ def test_plantcv_annotate_points_correct_mask(test_data): counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") - corrected_mask = counter.correct_mask(bin_img=discs, bin_img_recover=allmask, coords=coor) + corrected_mask = counter.correct_mask(bin_img=discs, bin_img_recover=allmask) assert np.count_nonzero(discs) < np.count_nonzero(corrected_mask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) \ No newline at end of file From 20b192fc37167b3e740e4ef91fbb1e77a2111a92 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 16:06:22 -0500 Subject: [PATCH 017/162] deepsource fixes --- plantcv/annotate/classes.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index a570518..2746330 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -218,19 +218,18 @@ def correct_mask(self, bin_img, bin_img_recover): y = int(y) totalcoor.append((y, x)) # Draw pt annotations onto a blank mask - pts_mask = cv2.circle(pts_mask, (x,y), radius=0, color=(255), thickness=-1) + pts_mask = cv2.circle(pts_mask, (x, y), radius=0, color=(255), thickness=-1) - # Only removes objects that were auto detected and then removed + # Only removes objects that were auto detected and then removed labeled_mask, total_obj_num = create_labels(mask=bin_img) # Objects that overlap with annotations get kept masked_image = apply_mask(img=labeled_mask, mask=pts_mask, mask_color='black') keep_object_ids = np.unique(masked_image) - for i in range(1,total_obj_num): + for i in range(1, total_obj_num): if i not in keep_object_ids: # Fill in objects that are not overlapping with an annotation labeled_mask[np.where(labeled_mask == i)] = 0 - #labeled_mask = np.where(labeled_mask == i, 0, labeled_mask) completed_mask = np.where(labeled_mask > 0, 255, 0) # points in class used for recovering and labeling From af0e28b351a21f1cbd6a478bb3d221001c37d2e1 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 14 May 2024 20:07:37 -0500 Subject: [PATCH 018/162] add coord trying to hit missed lines of coverage --- tests/test_annotate_points.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index f6175cf..2ed9e4c 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -169,7 +169,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): totalpoints1 = [(158, 531), (361, 112), (500, 418), (269.25303806488864, 385.69839981447126), (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963), (240.49608073650273, 277.1640769944342), (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), (423.24190633947126, 364.3625927643785), - (509.5127783246289, 353.2308673469388), (527, 275), (445.50535717435065, 138.94515306122452)] + (509.5127783246289, 353.2308673469388), (527, 275), (445.50535717435065, 138.94515306122452), (500,500)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") From c92a88d0f3e2b08867eafcc91e79c5ee242ab842 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 06:50:22 -0500 Subject: [PATCH 019/162] delete _remove_points --- plantcv/annotate/classes.py | 25 ++----------------------- 1 file changed, 2 insertions(+), 23 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 2746330..0912ef9 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -13,27 +13,6 @@ from plantcv.plantcv import create_labels, apply_mask -def _remove_points(autolist, confirmedlist): - """Function to remove points if interactively removed by user - Inputs: - autolist = total list of coordinates, automatically generated - from the contents of coords attribute - confirmedlist = coordinates of 'auto' detected points (e.g. coordinate - output of pcv.filters.eccentricity) - Returns: - removecoor = list of coordinates (of objects to remove from the binary mask) - :param autolist: list - :param confirmedlist: list - :return removecoor: list - """ - # internal function to remove to remove points specified by a user - removecoor = [] - for element in autolist: - if element not in confirmedlist: - removecoor.append(element) - return removecoor - - class Points: """Point annotation/collection class to use in Jupyter notebooks. It allows the user to interactively click to collect coordinates from an image. Left click collects the point and @@ -253,13 +232,13 @@ def correct_mask(self, bin_img, bin_img_recover): for id in unrecovered_ids: (x, y) = self.coords[names][id] unrec_points.append((x, y)) - new_name = str(names) + "_unrecovered" # Put unrecovered coords into new class - self.coords[new_name] = unrec_points + self.coords[str(names)+"_unrecovered"] = unrec_points # Overwrite attribute, only coords that have corresponding objects in the completed_mask new_points = [] for i, (x, y) in enumerate(self.coords[names]): if i not in unrecovered_ids: + print("line_hit") new_points.append((x, y)) self.coords[names] = new_points From d0be7f180089c4dc225c15881a678ac0a8c64204 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 06:50:39 -0500 Subject: [PATCH 020/162] add another click to test trying to inc coverage --- tests/test_annotate_points.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 2ed9e4c..a2f5f81 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -166,7 +166,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): # generate fake testing image allmask = cv2.imread(test_data.pollen_all, -1) discs = cv2.imread(test_data.pollen_discs, -1) - totalpoints1 = [(158, 531), (361, 112), (500, 418), (269.25303806488864, 385.69839981447126), + totalpoints1 = [(158, 531), (361, 112), (500, 418), (269.25303806488864, 385.69839981447126), (70,240), (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963), (240.49608073650273, 277.1640769944342), (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), (423.24190633947126, 364.3625927643785), (509.5127783246289, 353.2308673469388), (527, 275), (445.50535717435065, 138.94515306122452), (500,500)] From 88bc4d6ffb94efaa035f144378846ffa9fbe896d Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 14:11:30 -0500 Subject: [PATCH 021/162] Create points_correct_mask.md --- docs/points_correct_mask.md | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 docs/points_correct_mask.md diff --git a/docs/points_correct_mask.md b/docs/points_correct_mask.md new file mode 100644 index 0000000..abfa1ea --- /dev/null +++ b/docs/points_correct_mask.md @@ -0,0 +1,5 @@ +## Correct a Mask using Point Annotations + +Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it is possible to interactively click to collect coordinates from an image, then use these coordinate to remove and recover objects from a binary mask. + +**plantcv.annotate.Points.correct_mask**(*bin_img, bin_img_recover*) From aaa9886864cebdb83eede20de653ec4358de0a6c Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 14:30:33 -0500 Subject: [PATCH 022/162] add more tot point_correct_mask.md --- docs/points_correct_mask.md | 50 +++++++++++++++++++++++++++++++++++++ 1 file changed, 50 insertions(+) diff --git a/docs/points_correct_mask.md b/docs/points_correct_mask.md index abfa1ea..1bd9a71 100644 --- a/docs/points_correct_mask.md +++ b/docs/points_correct_mask.md @@ -3,3 +3,53 @@ Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it is possible to interactively click to collect coordinates from an image, then use these coordinate to remove and recover objects from a binary mask. **plantcv.annotate.Points.correct_mask**(*bin_img, bin_img_recover*) + +**returns** corrected_mask + +- **Parameters:** + - bin_img - binary image, filtered mask image with selected objects + - bin_img_recover - binary image, unclean mask image with all potentially recoverable objects + +- **Context:** + - Adds objects back to the `bin_mask` if they overlap with an annotation in the [`Points` class instance](Points.md) and can be recovered from the unclean mask `bin_img_recover`. Also checks each object in `bin_mask` and removes + it in the `corrected_mask` if there is not a corresponding annotation. + +- **Example use:** + - Remove noise from a microscopy image that is otherwise difficult to filter out with traditional computer vision + techniques, and recover stomata that were filtered out during mask cleaning. + +**Original Image with Annotations** + +![Screenshot](img/documentation_images/points_correct_mask/) + +**bin_img** + +![Screenshot](img/documentation_images/points_correct_mask/) + +**bin_img_recover** + +![Screenshot](img/documentation_images/points_correct_mask/) + +```python +import plantcv.plantcv as pcv +import plantcv.annotate as pcvan + +# Create an instance of the Points class +img, path, name = pcv.readimage("stomata.tif") + +# Segmentation & mask clean up steps here + +# Create an instance of the Points class & click on stomata +marker = pcvan.Points(img=img, figsize=(12,6)) + +corrected_mask = marker.correct_mask(bin_img=mask_clean, bin_img_recover=bin_img_recover) + +``` + +**Corrected Mask** + +![Screenshot](img/documentation_images/points_correct_mask/) + + +**Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annotate/classes.py) + From 68ae1277ab04dfdbdc75dbb5119e8cf8306ac411 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 14:30:51 -0500 Subject: [PATCH 023/162] Update Points.md minor context update to example use section --- docs/Points.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/Points.md b/docs/Points.md index 0d1d169..48f65da 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -28,7 +28,7 @@ closest collected point. - - **Example use:** - (pcv.roi.multi) - - (pcv.roi.custom) + - Shown below (pcv.roi.custom) ```python From 6822957f4bccb3d6ca598f757034a6be4d163a3e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 14:56:40 -0500 Subject: [PATCH 024/162] add doc image for mask correction --- .../points_correct_mask/annotated_stomata.png | Bin 0 -> 133551 bytes .../points_correct_mask/bin_img.png | Bin 0 -> 16689 bytes .../points_correct_mask/bin_img_recover.png | Bin 0 -> 31507 bytes .../points_correct_mask/corrected_mask.png | Bin 0 -> 12499 bytes .../points_correct_mask/overlay.png | Bin 0 -> 150129 bytes 5 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 docs/img/documentation_images/points_correct_mask/annotated_stomata.png create mode 100644 docs/img/documentation_images/points_correct_mask/bin_img.png create mode 100644 docs/img/documentation_images/points_correct_mask/bin_img_recover.png create mode 100644 docs/img/documentation_images/points_correct_mask/corrected_mask.png create mode 100644 docs/img/documentation_images/points_correct_mask/overlay.png diff --git a/docs/img/documentation_images/points_correct_mask/annotated_stomata.png b/docs/img/documentation_images/points_correct_mask/annotated_stomata.png new file mode 100644 index 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zLG;!oZax}|b>xb3QrC|a!zD+oaNT8v1FVw>(C)mpM2?hQ4k#llV@=db)(`G@bl{|Bv8uRj0) literal 0 HcmV?d00001 From 448f2e4ed626c46876848913a9fddfe745c7f882 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 14:57:09 -0500 Subject: [PATCH 025/162] include screenshots in points_correct_mask.md --- docs/points_correct_mask.md | 13 +++++++++---- 1 file changed, 9 insertions(+), 4 deletions(-) diff --git a/docs/points_correct_mask.md b/docs/points_correct_mask.md index 1bd9a71..df72814 100644 --- a/docs/points_correct_mask.md +++ b/docs/points_correct_mask.md @@ -20,15 +20,15 @@ Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it **Original Image with Annotations** -![Screenshot](img/documentation_images/points_correct_mask/) +![Screenshot](img/documentation_images/points_correct_mask/annotated_stomata.png) **bin_img** -![Screenshot](img/documentation_images/points_correct_mask/) +![Screenshot](img/documentation_images/points_correct_mask/bin_img.png) **bin_img_recover** -![Screenshot](img/documentation_images/points_correct_mask/) +![Screenshot](img/documentation_images/points_correct_mask/bin_img_recover.png) ```python import plantcv.plantcv as pcv @@ -44,11 +44,16 @@ marker = pcvan.Points(img=img, figsize=(12,6)) corrected_mask = marker.correct_mask(bin_img=mask_clean, bin_img_recover=bin_img_recover) +debug_vis = pcv.visualize.overlay_two_imgs(img, corrected_mask, alpha=.4) ``` **Corrected Mask** -![Screenshot](img/documentation_images/points_correct_mask/) +![Screenshot](img/documentation_images/points_correct_mask/corrected_mask.png) + +**Overlaid Image** + +![Screenshot](img/documentation_images/points_correct_mask/overlay.png) **Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annotate/classes.py) From 6ee2fd78a68d4255ed6ad13f57a998f7fb537b03 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 14:57:54 -0500 Subject: [PATCH 026/162] stop casting to 0/1 bin and keep 0/255 --- plantcv/annotate/classes.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 0912ef9..0101cfe 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -242,12 +242,10 @@ def correct_mask(self, bin_img, bin_img_recover): new_points.append((x, y)) self.coords[names] = new_points - completed_mask1 = 1*((completed_mask + 1*(completed_mask == 255)) != 0).astype(np.uint8) - params.debug = debug - _debug(visual=completed_mask1, + _debug(visual=completed_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) - return completed_mask1 + return completed_mask From e6f26bf9c4c3f0ba8aa992a1a91c82ccc382749e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 16:03:26 -0500 Subject: [PATCH 027/162] Update mkdocs.yml --- mkdocs.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/mkdocs.yml b/mkdocs.yml index eff0192..094a717 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -22,6 +22,7 @@ nav: - Napari Label: napari_label_classes.md - Napari Open: napari_open.md - Points: Points.md + - Points Correct Mask: points_correct_mask.md - Get Centroids: get_centroids.md markdown_extensions: - toc: From ebfba740e60b2169144c1226a6948662f74f4819 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 15 May 2024 16:03:45 -0500 Subject: [PATCH 028/162] remove coord trying to hit line 211 --- tests/test_annotate_points.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index a2f5f81..0c8b79c 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -168,7 +168,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): discs = cv2.imread(test_data.pollen_discs, -1) totalpoints1 = [(158, 531), (361, 112), (500, 418), (269.25303806488864, 385.69839981447126), (70,240), (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963), (240.49608073650273, 277.1640769944342), - (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), (423.24190633947126, 364.3625927643785), + (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), (509.5127783246289, 353.2308673469388), (527, 275), (445.50535717435065, 138.94515306122452), (500,500)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") From c97669e1d19b04eb36492d64c1d980525ce3eba4 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 16 May 2024 09:25:42 -0500 Subject: [PATCH 029/162] update test for last line hit --- tests/test_annotate_points.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 0c8b79c..0049fd1 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -166,10 +166,10 @@ def test_plantcv_annotate_points_correct_mask(test_data): # generate fake testing image allmask = cv2.imread(test_data.pollen_all, -1) discs = cv2.imread(test_data.pollen_discs, -1) - totalpoints1 = [(158, 531), (361, 112), (500, 418), (269.25303806488864, 385.69839981447126), (70,240), + totalpoints1 = [(361, 112), (500, 418), (269.25303806488864, 385.69839981447126), (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963), (240.49608073650273, 277.1640769944342), (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), - (509.5127783246289, 353.2308673469388), (527, 275), (445.50535717435065, 138.94515306122452), (500,500)] + (509.5127783246289, 353.2308673469388), (527, 275), (500,500)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") From 65f58de6fac48300088f538e2340b09feca945ba Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 16 May 2024 09:25:52 -0500 Subject: [PATCH 030/162] remove print statement --- plantcv/annotate/classes.py | 1 - 1 file changed, 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 0101cfe..da23ec8 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -238,7 +238,6 @@ def correct_mask(self, bin_img, bin_img_recover): new_points = [] for i, (x, y) in enumerate(self.coords[names]): if i not in unrecovered_ids: - print("line_hit") new_points.append((x, y)) self.coords[names] = new_points From b3ae7f7e930e9dab5ef1e43eb4bfef451f7ced88 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 16 May 2024 14:54:51 -0500 Subject: [PATCH 031/162] update test based on changes to main --- tests/test_annotate_points.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index c045f45..eea6adf 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -156,7 +156,7 @@ def test_points_view_warn(test_data): e1.xdata, e1.ydata = point1 drawer_rgb.onclick(e1) drawer_rgb.view(label="new", color='r') - assert str(drawer_rgb.fig) == "Figure(1200x600)" + assert str(drawer_rgb.fig) == "Figure(500x500)" def test_plantcv_annotate_points_correct_mask(test_data): From 15f3b5aa77905b9adaf70da2400248d46abc28f5 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 16 May 2024 16:04:56 -0500 Subject: [PATCH 032/162] add timer, temp --- plantcv/annotate/classes.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index da23ec8..345657b 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -11,6 +11,8 @@ from plantcv.plantcv import warn, params from plantcv.plantcv._debug import _debug from plantcv.plantcv import create_labels, apply_mask +import time + class Points: @@ -178,6 +180,7 @@ def correct_mask(self, bin_img, bin_img_recover): completed_mask : numpy.ndarray corrected binary mask with recovered and removed objects """ + tic = time.perf_counter() from plantcv.plantcv.floodfill import floodfill debug = params.debug @@ -246,5 +249,6 @@ def correct_mask(self, bin_img, bin_img_recover): _debug(visual=completed_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) - + toc = time.perf_counter() + print(f"Function ran in {toc - tic:0.4f} seconds") return completed_mask From 9af32ecaf80b73b15ed95cbd68dc0fb62feb36d0 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 22 May 2024 14:16:00 -0500 Subject: [PATCH 033/162] add shorter correction method --- plantcv/annotate/classes.py | 44 +++++++++++++++++++++++++++++++++++++ 1 file changed, 44 insertions(+) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 345657b..50eb794 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -252,3 +252,47 @@ def correct_mask(self, bin_img, bin_img_recover): toc = time.perf_counter() print(f"Function ran in {toc - tic:0.4f} seconds") return completed_mask + + def correct_mask2(self, bin_img): + """View coordinates for a specific class label. + + Parameters + ---------- + bin_img : numpy.ndarray + binary image, filtered mask image with selected objects + bin_img_recover : numpy.ndarray + binary image, unclean mask image with all potential objects + + Returns + ---------- + completed_mask : numpy.ndarray + corrected binary mask with recovered and removed objects + """ + from skimage.color import label2rgb + from skimage.measure import label + + tic = time.perf_counter() + # Output mask + outmask = np.zeros(bin_img.shape) + # Annotation mask + ptmask = np.zeros(bin_img.shape, dtype=np.uint8) + + # Add one pixel to the annotation mask for each point + for lbl in self.coords: + for x, y in self.coords[lbl]: + ptmask[y, x] = 255 + + # Create a labeled mask from the input mask + labeled_mask, num_labels = label(bin_img, background=0, return_num=True, connectivity=2) + # Filter the mask based on annotations + for i in range(1, num_labels + 1): + if np.max(ptmask[np.where(labeled_mask == i)]) == 255: + outmask[np.where(labeled_mask == i)] = i + # Debug output + colorful = label2rgb(outmask) + colorful = ((255*colorful).astype(np.uint8)) + _debug(visual=colorful, filename=os.path.join(pcv.params.debug_outdir, f"{pcv.params.device}_corrected_labeled_mask.png")) + + toc = time.perf_counter() + print(f"Function ran in {toc - tic:0.4f} seconds") + return outmask From bbf2a05eab71559dfe247b8e0b6f972e232677f1 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 22 May 2024 15:15:13 -0500 Subject: [PATCH 034/162] remove extra bin_img from correct_mask assuming that bin_img was a subset of bin_img_recover means that bin_img is not useful with this method --- plantcv/annotate/classes.py | 13 ++++--------- 1 file changed, 4 insertions(+), 9 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 50eb794..7e730b9 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -165,7 +165,7 @@ class label, by default "default" for (x, y) in self.coords[self.label]: self.ax.plot(x, y, marker='x', c=self.color) - def correct_mask(self, bin_img, bin_img_recover): + def correct_mask(self, bin_img): """View coordinates for a specific class label. Parameters @@ -219,13 +219,7 @@ def correct_mask(self, bin_img, bin_img_recover): for i, (x, y) in enumerate(self.coords[names]): x = int(x) y = int(y) - # corrected coordinates - if completed_mask[y, x] == 0 and bin_img_recover[y, x] > 0: - print(f"Recovering object at coordinate: x = {x}, y = {y}") - total_mask_minus_objs = floodfill(bin_img_recover, [(x, y)], 0) - recovered_objs = bin_img_recover - total_mask_minus_objs - completed_mask = completed_mask + recovered_objs - elif completed_mask[y, x] == 0 and bin_img_recover[y, x] == 0: + if completed_mask[y, x] == 0 and bin_img[y, x] == 0: print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) @@ -291,7 +285,8 @@ def correct_mask2(self, bin_img): # Debug output colorful = label2rgb(outmask) colorful = ((255*colorful).astype(np.uint8)) - _debug(visual=colorful, filename=os.path.join(pcv.params.debug_outdir, f"{pcv.params.device}_corrected_labeled_mask.png")) + _debug(visual=colorful, + filename=os.path.join(params.debug_outdir, f"{params.device}_corrected_labeled_mask.png")) toc = time.perf_counter() print(f"Function ran in {toc - tic:0.4f} seconds") From 8d96d84574cd04806a48d0701abbf3bb216e073f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 22 May 2024 15:22:54 -0500 Subject: [PATCH 035/162] update inputs for unit test --- tests/test_annotate_points.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index eea6adf..3d88d4d 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -172,7 +172,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") - corrected_mask = counter.correct_mask(bin_img=discs, bin_img_recover=allmask) + corrected_mask = counter.correct_mask(bin_img=allmask) assert np.count_nonzero(discs) < np.count_nonzero(corrected_mask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) From ca3b2d343db5dcb0c0391618374b7e4369ca29fe Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 23 May 2024 10:53:21 -0500 Subject: [PATCH 036/162] add class labels to running list and return them --- plantcv/annotate/classes.py | 30 +++++++++++++++++++++--------- 1 file changed, 21 insertions(+), 9 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 7e730b9..9e23ea5 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -182,9 +182,10 @@ def correct_mask(self, bin_img): """ tic = time.perf_counter() from plantcv.plantcv.floodfill import floodfill + from plantcv.plantcv import plot_image - debug = params.debug - params.debug = None + # debug = params.debug + # params.debug = None labelnames = list(self.count) @@ -192,6 +193,8 @@ def correct_mask(self, bin_img): totalcoor = [] unrecovered_ids = [] + list_labels = [] + total_pts_num = sum(self.count.values()) pts_mask = np.zeros(np.shape(bin_img)) for names in labelnames: @@ -201,19 +204,22 @@ def correct_mask(self, bin_img): totalcoor.append((y, x)) # Draw pt annotations onto a blank mask pts_mask = cv2.circle(pts_mask, (x, y), radius=0, color=(255), thickness=-1) - # Only removes objects that were auto detected and then removed labeled_mask, total_obj_num = create_labels(mask=bin_img) # Objects that overlap with annotations get kept masked_image = apply_mask(img=labeled_mask, mask=pts_mask, mask_color='black') keep_object_ids = np.unique(masked_image) - for i in range(1, total_obj_num): + for i in range(1, total_obj_num + 1): if i not in keep_object_ids: # Fill in objects that are not overlapping with an annotation + print("removing an object from the mask") labeled_mask[np.where(labeled_mask == i)] = 0 - completed_mask = np.where(labeled_mask > 0, 255, 0) + #completed_mask = np.where(labeled_mask > 0, 255, 0) + completed_mask = np.copy(labeled_mask) + + object_count = 1 # points in class used for recovering and labeling for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -222,13 +228,19 @@ def correct_mask(self, bin_img): if completed_mask[y, x] == 0 and bin_img[y, x] == 0: print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) + else: + list_labels.append(str(object_count)+"_"+names) + object_count += 1 # Split up "coords" attribute into two classes if len(unrecovered_ids) > 0: unrec_points = [] - for id in unrecovered_ids: + for j, id in enumerate(unrecovered_ids): (x, y) = self.coords[names][id] unrec_points.append((x, y)) + # draw a labeled pixel, pix value unique to those found in labeled_mask from bin_img + completed_mask[y, x] = total_pts_num + j + list_labels.append(str(object_count)+"_"+names+"_unrecovered") # Put unrecovered coords into new class self.coords[str(names)+"_unrecovered"] = unrec_points # Overwrite attribute, only coords that have corresponding objects in the completed_mask @@ -238,14 +250,14 @@ def correct_mask(self, bin_img): new_points.append((x, y)) self.coords[names] = new_points - params.debug = debug - + #params.debug = debug + print(list_labels) _debug(visual=completed_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) toc = time.perf_counter() print(f"Function ran in {toc - tic:0.4f} seconds") - return completed_mask + return completed_mask, list_labels def correct_mask2(self, bin_img): """View coordinates for a specific class label. From 629276bbf46f1c47d233c7d7e2f00b8857fbcdf5 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 23 May 2024 11:16:56 -0500 Subject: [PATCH 037/162] update ID numbering for labels and labeled mask --- plantcv/annotate/classes.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 9e23ea5..57ead3b 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -219,7 +219,7 @@ def correct_mask(self, bin_img): #completed_mask = np.where(labeled_mask > 0, 255, 0) completed_mask = np.copy(labeled_mask) - object_count = 1 + object_count = 0 # points in class used for recovering and labeling for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -235,7 +235,7 @@ def correct_mask(self, bin_img): # Split up "coords" attribute into two classes if len(unrecovered_ids) > 0: unrec_points = [] - for j, id in enumerate(unrecovered_ids): + for j, id in enumerate(unrecovered_ids, start=0): (x, y) = self.coords[names][id] unrec_points.append((x, y)) # draw a labeled pixel, pix value unique to those found in labeled_mask from bin_img From e18a21f55d796a9b513f2aeb54411c2ed8938ae5 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 23 May 2024 11:54:02 -0500 Subject: [PATCH 038/162] add logic to check for multiple annotations in one region of the labeled mask --- plantcv/annotate/classes.py | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 57ead3b..39a5295 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -208,7 +208,8 @@ def correct_mask(self, bin_img): labeled_mask, total_obj_num = create_labels(mask=bin_img) # Objects that overlap with annotations get kept masked_image = apply_mask(img=labeled_mask, mask=pts_mask, mask_color='black') - keep_object_ids = np.unique(masked_image) + keep_object_ids, counts = np.unique(masked_image, return_counts=True) + print(counts) for i in range(1, total_obj_num + 1): if i not in keep_object_ids: @@ -229,7 +230,14 @@ def correct_mask(self, bin_img): print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) else: - list_labels.append(str(object_count)+"_"+names) + mask_pixel_value = completed_mask[y, x] + print(counts[mask_pixel_value]) + if counts[mask_pixel_value] == 1: + list_labels.append(str(object_count)+"_"+names) + else: + multiple_labels = np.where(masked_image == mask_pixel_value) + print(multiple_labels) + # else combine labels object_count += 1 # Split up "coords" attribute into two classes From b370e68e6a124db1e4183acb1a72aa1874dbd63e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 23 May 2024 15:38:19 -0500 Subject: [PATCH 039/162] remove some of the troubleshooting code --- plantcv/annotate/classes.py | 59 +++++-------------------------------- 1 file changed, 8 insertions(+), 51 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 39a5295..8a8f4d2 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -184,8 +184,8 @@ def correct_mask(self, bin_img): from plantcv.plantcv.floodfill import floodfill from plantcv.plantcv import plot_image - # debug = params.debug - # params.debug = None + debug = params.debug + params.debug = None labelnames = list(self.count) @@ -209,12 +209,11 @@ def correct_mask(self, bin_img): # Objects that overlap with annotations get kept masked_image = apply_mask(img=labeled_mask, mask=pts_mask, mask_color='black') keep_object_ids, counts = np.unique(masked_image, return_counts=True) - print(counts) for i in range(1, total_obj_num + 1): if i not in keep_object_ids: # Fill in objects that are not overlapping with an annotation - print("removing an object from the mask") + print("filtering un-annotated object from the mask") labeled_mask[np.where(labeled_mask == i)] = 0 #completed_mask = np.where(labeled_mask > 0, 255, 0) @@ -232,10 +231,14 @@ def correct_mask(self, bin_img): else: mask_pixel_value = completed_mask[y, x] print(counts[mask_pixel_value]) + # if only one annotation overlap, then done, add label to list if counts[mask_pixel_value] == 1: list_labels.append(str(object_count)+"_"+names) + # otherwise combine labels if classes unique & drop labels in not unique + # can we draw "unresolved" annotations where the duplicate labels happen? else: multiple_labels = np.where(masked_image == mask_pixel_value) + # get coordinate info and trace back to find class label name print(multiple_labels) # else combine labels object_count += 1 @@ -258,56 +261,10 @@ def correct_mask(self, bin_img): new_points.append((x, y)) self.coords[names] = new_points - #params.debug = debug - print(list_labels) + params.debug = debug _debug(visual=completed_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) toc = time.perf_counter() print(f"Function ran in {toc - tic:0.4f} seconds") return completed_mask, list_labels - - def correct_mask2(self, bin_img): - """View coordinates for a specific class label. - - Parameters - ---------- - bin_img : numpy.ndarray - binary image, filtered mask image with selected objects - bin_img_recover : numpy.ndarray - binary image, unclean mask image with all potential objects - - Returns - ---------- - completed_mask : numpy.ndarray - corrected binary mask with recovered and removed objects - """ - from skimage.color import label2rgb - from skimage.measure import label - - tic = time.perf_counter() - # Output mask - outmask = np.zeros(bin_img.shape) - # Annotation mask - ptmask = np.zeros(bin_img.shape, dtype=np.uint8) - - # Add one pixel to the annotation mask for each point - for lbl in self.coords: - for x, y in self.coords[lbl]: - ptmask[y, x] = 255 - - # Create a labeled mask from the input mask - labeled_mask, num_labels = label(bin_img, background=0, return_num=True, connectivity=2) - # Filter the mask based on annotations - for i in range(1, num_labels + 1): - if np.max(ptmask[np.where(labeled_mask == i)]) == 255: - outmask[np.where(labeled_mask == i)] = i - # Debug output - colorful = label2rgb(outmask) - colorful = ((255*colorful).astype(np.uint8)) - _debug(visual=colorful, - filename=os.path.join(params.debug_outdir, f"{params.device}_corrected_labeled_mask.png")) - - toc = time.perf_counter() - print(f"Function ran in {toc - tic:0.4f} seconds") - return outmask From 615c0f8660ae3ac36bcd4499b45a0cf16323922e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 4 Jun 2024 11:46:50 -0500 Subject: [PATCH 040/162] Update classes.py --- plantcv/annotate/classes.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 8a8f4d2..85838d3 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -216,8 +216,10 @@ def correct_mask(self, bin_img): print("filtering un-annotated object from the mask") labeled_mask[np.where(labeled_mask == i)] = 0 - #completed_mask = np.where(labeled_mask > 0, 255, 0) - completed_mask = np.copy(labeled_mask) + completed_mask_bin = np.where(labeled_mask > 0, 255, 0) + labeled_mask_all, _ = create_labels(mask=completed_mask_bin) + completed_mask = np.copy(labeled_mask_all) + pix_vals, counts = np.unique(completed_mask, return_counts=True) object_count = 0 # points in class used for recovering and labeling From 1e7e890eff1fbcf46d8fbe636d328143d8f4e0e9 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 26 Jun 2024 10:13:58 -0500 Subject: [PATCH 041/162] capture second output in test --- tests/test_annotate_points.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 3d88d4d..b4c47a3 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -172,7 +172,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") - corrected_mask = counter.correct_mask(bin_img=allmask) + corrected_mask, _ = counter.correct_mask(bin_img=allmask) assert np.count_nonzero(discs) < np.count_nonzero(corrected_mask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) From 1d8d83f13d7db8d95a82de870c944941f830851e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 26 Jun 2024 10:47:03 -0500 Subject: [PATCH 042/162] remove timer and capture unused var --- plantcv/annotate/classes.py | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 85838d3..94066b7 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -180,10 +180,6 @@ def correct_mask(self, bin_img): completed_mask : numpy.ndarray corrected binary mask with recovered and removed objects """ - tic = time.perf_counter() - from plantcv.plantcv.floodfill import floodfill - from plantcv.plantcv import plot_image - debug = params.debug params.debug = None @@ -219,7 +215,7 @@ def correct_mask(self, bin_img): completed_mask_bin = np.where(labeled_mask > 0, 255, 0) labeled_mask_all, _ = create_labels(mask=completed_mask_bin) completed_mask = np.copy(labeled_mask_all) - pix_vals, counts = np.unique(completed_mask, return_counts=True) + _, counts = np.unique(completed_mask, return_counts=True) object_count = 0 # points in class used for recovering and labeling @@ -267,6 +263,4 @@ def correct_mask(self, bin_img): _debug(visual=completed_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) - toc = time.perf_counter() - print(f"Function ran in {toc - tic:0.4f} seconds") return completed_mask, list_labels From 0ef5b9fd575d98386530b87ee86b48fb04f63894 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 26 Jun 2024 10:49:17 -0500 Subject: [PATCH 043/162] remove whitespace and unused import --- plantcv/annotate/classes.py | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 94066b7..d30243d 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -11,8 +11,6 @@ from plantcv.plantcv import warn, params from plantcv.plantcv._debug import _debug from plantcv.plantcv import create_labels, apply_mask -import time - class Points: @@ -189,7 +187,7 @@ def correct_mask(self, bin_img): totalcoor = [] unrecovered_ids = [] - list_labels = [] + list_labels = [] total_pts_num = sum(self.count.values()) pts_mask = np.zeros(np.shape(bin_img)) @@ -229,16 +227,16 @@ def correct_mask(self, bin_img): else: mask_pixel_value = completed_mask[y, x] print(counts[mask_pixel_value]) - # if only one annotation overlap, then done, add label to list + # if only one annotation overlap, then done, add label to list if counts[mask_pixel_value] == 1: list_labels.append(str(object_count)+"_"+names) # otherwise combine labels if classes unique & drop labels in not unique - # can we draw "unresolved" annotations where the duplicate labels happen? + # can we draw "unresolved" annotations where the duplicate labels happen? else: multiple_labels = np.where(masked_image == mask_pixel_value) # get coordinate info and trace back to find class label name print(multiple_labels) - # else combine labels + # else combine labels ? object_count += 1 # Split up "coords" attribute into two classes From 350fe1244d2dcca6b3309d8b512daf4eb7e7f0df Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 27 Jun 2024 12:54:57 -0500 Subject: [PATCH 044/162] remove point annotation trying to hit last line of code w test --- tests/test_annotate_points.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index b4c47a3..a9fdbf3 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -165,10 +165,10 @@ def test_plantcv_annotate_points_correct_mask(test_data): # generate fake testing image allmask = cv2.imread(test_data.pollen_all, -1) discs = cv2.imread(test_data.pollen_discs, -1) - totalpoints1 = [(361, 112), (500, 418), (269.25303806488864, 385.69839981447126), + totalpoints1 = [(500, 418), (269.25303806488864, 385.69839981447126), (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963), (240.49608073650273, 277.1640769944342), (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), - (509.5127783246289, 353.2308673469388), (527, 275), (500,500)] + (509.5127783246289, 353.2308673469388), (500,500)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") From 9680acd016786521087d10db8a7e69ddff009075 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 27 Jun 2024 13:33:19 -0500 Subject: [PATCH 045/162] test coverage attempt, replace coords? --- tests/test_annotate_points.py | 19 +++++++++++++++---- 1 file changed, 15 insertions(+), 4 deletions(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index a9fdbf3..926e9c4 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -165,10 +165,21 @@ def test_plantcv_annotate_points_correct_mask(test_data): # generate fake testing image allmask = cv2.imread(test_data.pollen_all, -1) discs = cv2.imread(test_data.pollen_discs, -1) - totalpoints1 = [(500, 418), (269.25303806488864, 385.69839981447126), - (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963), (240.49608073650273, 277.1640769944342), - (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), - (509.5127783246289, 353.2308673469388), (500,500)] + totalpoints1 = [(116, 47), + (322, 46), + (364, 109), + (286, 152), + (266, 174), + (305, 196), + (184, 156), + (162, 185), + (65, 189), + (70, 241), + (100, 299), + (186, 351), + (242, 340), + (247, 281), + (279, 337)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") From acc18d3345c045a8be59193124923549a87f8f19 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 27 Jun 2024 13:40:24 -0500 Subject: [PATCH 046/162] test logic reversed --- tests/test_annotate_points.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 926e9c4..d3580dd 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -184,6 +184,6 @@ def test_plantcv_annotate_points_correct_mask(test_data): counter.import_list(totalpoints1, label="total") corrected_mask, _ = counter.correct_mask(bin_img=allmask) - assert np.count_nonzero(discs) < np.count_nonzero(corrected_mask) + assert np.count_nonzero(corrected_mask) < np.count_nonzero(discs) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) From 000504aa6d6bee5353a341d79415862c96735f8b Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 15 Jul 2024 14:35:38 -0500 Subject: [PATCH 047/162] correct_mask returns a labeled mask re-identify object labels after un-annotated object filtered out, then find new labeled overlap mask --- plantcv/annotate/classes.py | 19 +++++++++---------- 1 file changed, 9 insertions(+), 10 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index d30243d..51f57f6 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -200,20 +200,21 @@ def correct_mask(self, bin_img): pts_mask = cv2.circle(pts_mask, (x, y), radius=0, color=(255), thickness=-1) # Only removes objects that were auto detected and then removed labeled_mask, total_obj_num = create_labels(mask=bin_img) + labeled_mask1 = np.copy(labeled_mask) # Objects that overlap with annotations get kept - masked_image = apply_mask(img=labeled_mask, mask=pts_mask, mask_color='black') + masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') keep_object_ids, counts = np.unique(masked_image, return_counts=True) for i in range(1, total_obj_num + 1): if i not in keep_object_ids: # Fill in objects that are not overlapping with an annotation print("filtering un-annotated object from the mask") - labeled_mask[np.where(labeled_mask == i)] = 0 + labeled_mask1[np.where(labeled_mask == i)] = 0 - completed_mask_bin = np.where(labeled_mask > 0, 255, 0) + completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) labeled_mask_all, _ = create_labels(mask=completed_mask_bin) - completed_mask = np.copy(labeled_mask_all) - _, counts = np.unique(completed_mask, return_counts=True) + labeled_annotation_overlap_mask = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') + id, counts = np.unique(labeled_annotation_overlap_mask, return_counts=True) object_count = 0 # points in class used for recovering and labeling @@ -225,8 +226,7 @@ def correct_mask(self, bin_img): print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) else: - mask_pixel_value = completed_mask[y, x] - print(counts[mask_pixel_value]) + mask_pixel_value = labeled_mask_all[y, x] # if only one annotation overlap, then done, add label to list if counts[mask_pixel_value] == 1: list_labels.append(str(object_count)+"_"+names) @@ -235,7 +235,6 @@ def correct_mask(self, bin_img): else: multiple_labels = np.where(masked_image == mask_pixel_value) # get coordinate info and trace back to find class label name - print(multiple_labels) # else combine labels ? object_count += 1 @@ -258,7 +257,7 @@ def correct_mask(self, bin_img): self.coords[names] = new_points params.debug = debug - _debug(visual=completed_mask, + _debug(visual=labeled_mask_all, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) - return completed_mask, list_labels + return labeled_mask_all, list_labels From ccc4f8e0532bdec70f79ff039666bec7ac158162 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 15 Jul 2024 16:04:07 -0500 Subject: [PATCH 048/162] add pixel annotation to labeled mask when unresolved object changing the logic a little and add in functionality to add pixel to annotations where no object can be resolved from the bin-mask --- plantcv/annotate/classes.py | 30 ++++++++++++++++++------------ 1 file changed, 18 insertions(+), 12 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 51f57f6..9742b7d 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -170,13 +170,11 @@ def correct_mask(self, bin_img): ---------- bin_img : numpy.ndarray binary image, filtered mask image with selected objects - bin_img_recover : numpy.ndarray - binary image, unclean mask image with all potential objects Returns ---------- - completed_mask : numpy.ndarray - corrected binary mask with recovered and removed objects + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects """ debug = params.debug params.debug = None @@ -190,6 +188,7 @@ def correct_mask(self, bin_img): list_labels = [] total_pts_num = sum(self.count.values()) pts_mask = np.zeros(np.shape(bin_img)) + final_mask = np.zeros(np.shape(bin_img)) for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -198,20 +197,22 @@ def correct_mask(self, bin_img): totalcoor.append((y, x)) # Draw pt annotations onto a blank mask pts_mask = cv2.circle(pts_mask, (x, y), radius=0, color=(255), thickness=-1) - # Only removes objects that were auto detected and then removed + # Create a labeled mask from the input mask labeled_mask, total_obj_num = create_labels(mask=bin_img) labeled_mask1 = np.copy(labeled_mask) - # Objects that overlap with annotations get kept + # Objects that overlap with one or more annotations get kept masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') - keep_object_ids, counts = np.unique(masked_image, return_counts=True) + keep_object_ids = np.unique(masked_image) + print(keep_object_ids) + # Fill in objects that are not overlapping with an annotation for i in range(1, total_obj_num + 1): if i not in keep_object_ids: - # Fill in objects that are not overlapping with an annotation print("filtering un-annotated object from the mask") labeled_mask1[np.where(labeled_mask == i)] = 0 - + # Create new binary mask after filtering un-annotated objects completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) + # Create a new labeled annotation mask to determine number of annotation per object labeled_mask_all, _ = create_labels(mask=completed_mask_bin) labeled_annotation_overlap_mask = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') id, counts = np.unique(labeled_annotation_overlap_mask, return_counts=True) @@ -225,8 +226,13 @@ def correct_mask(self, bin_img): if completed_mask[y, x] == 0 and bin_img[y, x] == 0: print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) + # Add a pixel where unresolved annotation to the mask + final_mask = cv2.circle(final_mask, (x, y), radius=0, color=(i), thickness=-1) + #final_mask[y, x] == i else: mask_pixel_value = labeled_mask_all[y, x] + # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) + final_mask = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) # if only one annotation overlap, then done, add label to list if counts[mask_pixel_value] == 1: list_labels.append(str(object_count)+"_"+names) @@ -235,7 +241,7 @@ def correct_mask(self, bin_img): else: multiple_labels = np.where(masked_image == mask_pixel_value) # get coordinate info and trace back to find class label name - # else combine labels ? + # combine labels from both classes object_count += 1 # Split up "coords" attribute into two classes @@ -257,7 +263,7 @@ def correct_mask(self, bin_img): self.coords[names] = new_points params.debug = debug - _debug(visual=labeled_mask_all, + _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) - return labeled_mask_all, list_labels + return final_mask, list_labels From 54344ce2217024a9d365460543afdc2f86be5a9e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 15 Jul 2024 16:26:28 -0500 Subject: [PATCH 049/162] add pseudocode placeholder that will get removed soon --- tests/test_annotate_points.py | 1 + 1 file changed, 1 insertion(+) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index d3580dd..07d8790 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -177,6 +177,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): (70, 241), (100, 299), (186, 351), + (188, 351), (242, 340), (247, 281), (279, 337)] From 458f4083ed2ee53ad06c85e9e9e33f1ab04c38f5 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 15 Jul 2024 16:27:22 -0500 Subject: [PATCH 050/162] deepsource edits but includes pseudo-code for complexity --- plantcv/annotate/classes.py | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 9742b7d..b090d3f 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -228,7 +228,6 @@ def correct_mask(self, bin_img): unrecovered_ids.append(i) # Add a pixel where unresolved annotation to the mask final_mask = cv2.circle(final_mask, (x, y), radius=0, color=(i), thickness=-1) - #final_mask[y, x] == i else: mask_pixel_value = labeled_mask_all[y, x] # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) @@ -239,9 +238,12 @@ def correct_mask(self, bin_img): # otherwise combine labels if classes unique & drop labels in not unique # can we draw "unresolved" annotations where the duplicate labels happen? else: - multiple_labels = np.where(masked_image == mask_pixel_value) - # get coordinate info and trace back to find class label name - # combine labels from both classes + #multiple_labels = np.where(masked_image == mask_pixel_value) + # get coordinate info and trace back to find class label name(s) + # combine labels from both classes if unique + #list_labels.append(combined_name) + # if not unique then skip all except the first? + print("Complex replicate handled") object_count += 1 # Split up "coords" attribute into two classes From eff96423167b302d9d6b0219f44eec357e4bba72 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 16 Jul 2024 13:40:33 -0500 Subject: [PATCH 051/162] update if statement, only need to check overlap with one mask now --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index b090d3f..fed4f4c 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -223,7 +223,7 @@ def correct_mask(self, bin_img): for i, (x, y) in enumerate(self.coords[names]): x = int(x) y = int(y) - if completed_mask[y, x] == 0 and bin_img[y, x] == 0: + if bin_img[y, x] == 0: print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) # Add a pixel where unresolved annotation to the mask From 773e6fb1dc9ae9019e2df70eff07fae092d1513c Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 16 Jul 2024 13:49:01 -0500 Subject: [PATCH 052/162] move what can be moved outside the "else" statement --- plantcv/annotate/classes.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index fed4f4c..11ddf5f 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -223,13 +223,13 @@ def correct_mask(self, bin_img): for i, (x, y) in enumerate(self.coords[names]): x = int(x) y = int(y) - if bin_img[y, x] == 0: + mask_pixel_value = labeled_mask_all[y, x] + if mask_pixel_value == 0: print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) # Add a pixel where unresolved annotation to the mask final_mask = cv2.circle(final_mask, (x, y), radius=0, color=(i), thickness=-1) else: - mask_pixel_value = labeled_mask_all[y, x] # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) final_mask = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) # if only one annotation overlap, then done, add label to list From bec7bbbf49537654b28054388ab1457011fa609c Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 16 Jul 2024 14:25:23 -0500 Subject: [PATCH 053/162] update ID in labeled for unrecovered annotations --- plantcv/annotate/classes.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 11ddf5f..ee70dcb 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -236,7 +236,6 @@ def correct_mask(self, bin_img): if counts[mask_pixel_value] == 1: list_labels.append(str(object_count)+"_"+names) # otherwise combine labels if classes unique & drop labels in not unique - # can we draw "unresolved" annotations where the duplicate labels happen? else: #multiple_labels = np.where(masked_image == mask_pixel_value) # get coordinate info and trace back to find class label name(s) @@ -254,7 +253,7 @@ def correct_mask(self, bin_img): unrec_points.append((x, y)) # draw a labeled pixel, pix value unique to those found in labeled_mask from bin_img completed_mask[y, x] = total_pts_num + j - list_labels.append(str(object_count)+"_"+names+"_unrecovered") + list_labels.append(str(id)+"_"+names+"_unrecovered") # Put unrecovered coords into new class self.coords[str(names)+"_unrecovered"] = unrec_points # Overwrite attribute, only coords that have corresponding objects in the completed_mask From 95670c0beef437403789d890ce4119ece42f886b Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 16 Jul 2024 14:51:56 -0500 Subject: [PATCH 054/162] sort labels based on annotation ID --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index ee70dcb..c59b260 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -267,4 +267,4 @@ def correct_mask(self, bin_img): _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) - return final_mask, list_labels + return final_mask, list_labels.sort() From 2f2ac0490b20639d3822935bca057de7fd285aa7 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 16 Jul 2024 15:06:53 -0500 Subject: [PATCH 055/162] sort command within function, otherwise return is null --- plantcv/annotate/classes.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index c59b260..94d3830 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -262,9 +262,10 @@ def correct_mask(self, bin_img): if i not in unrecovered_ids: new_points.append((x, y)) self.coords[names] = new_points - + + list_labels.sort() params.debug = debug _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) - return final_mask, list_labels.sort() + return final_mask, list_labels From cff1cf3e75751787dbd44580326df2f006b735ff Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 16 Jul 2024 16:16:09 -0500 Subject: [PATCH 056/162] remove print statement for unique IDs --- plantcv/annotate/classes.py | 1 - 1 file changed, 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 94d3830..7c89330 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -203,7 +203,6 @@ def correct_mask(self, bin_img): # Objects that overlap with one or more annotations get kept masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') keep_object_ids = np.unique(masked_image) - print(keep_object_ids) # Fill in objects that are not overlapping with an annotation for i in range(1, total_obj_num + 1): From 698717e161b8bac9ed4457a0681eda25fb2461dd Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 17 Jul 2024 15:20:53 -0500 Subject: [PATCH 057/162] delete whitespace --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 7c89330..282f6fd 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -261,7 +261,7 @@ def correct_mask(self, bin_img): if i not in unrecovered_ids: new_points.append((x, y)) self.coords[names] = new_points - + list_labels.sort() params.debug = debug _debug(visual=final_mask, From fed91c99772cabd102a470e5a4d76ba65a41ed09 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 17 Jul 2024 15:56:25 -0500 Subject: [PATCH 058/162] NEW APPROACH - only mask filtering update function code and unit test --- plantcv/annotate/classes.py | 44 ++--------------------------------- tests/test_annotate_points.py | 2 +- 2 files changed, 3 insertions(+), 43 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 282f6fd..5f3a670 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -180,13 +180,8 @@ def correct_mask(self, bin_img): params.debug = None labelnames = list(self.count) - - completed_mask = np.copy(bin_img) - totalcoor = [] unrecovered_ids = [] - list_labels = [] - total_pts_num = sum(self.count.values()) pts_mask = np.zeros(np.shape(bin_img)) final_mask = np.zeros(np.shape(bin_img)) @@ -207,16 +202,12 @@ def correct_mask(self, bin_img): # Fill in objects that are not overlapping with an annotation for i in range(1, total_obj_num + 1): if i not in keep_object_ids: - print("filtering un-annotated object from the mask") labeled_mask1[np.where(labeled_mask == i)] = 0 # Create new binary mask after filtering un-annotated objects completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) # Create a new labeled annotation mask to determine number of annotation per object labeled_mask_all, _ = create_labels(mask=completed_mask_bin) - labeled_annotation_overlap_mask = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') - id, counts = np.unique(labeled_annotation_overlap_mask, return_counts=True) - object_count = 0 # points in class used for recovering and labeling for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -231,40 +222,9 @@ def correct_mask(self, bin_img): else: # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) final_mask = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) - # if only one annotation overlap, then done, add label to list - if counts[mask_pixel_value] == 1: - list_labels.append(str(object_count)+"_"+names) - # otherwise combine labels if classes unique & drop labels in not unique - else: - #multiple_labels = np.where(masked_image == mask_pixel_value) - # get coordinate info and trace back to find class label name(s) - # combine labels from both classes if unique - #list_labels.append(combined_name) - # if not unique then skip all except the first? - print("Complex replicate handled") - object_count += 1 - - # Split up "coords" attribute into two classes - if len(unrecovered_ids) > 0: - unrec_points = [] - for j, id in enumerate(unrecovered_ids, start=0): - (x, y) = self.coords[names][id] - unrec_points.append((x, y)) - # draw a labeled pixel, pix value unique to those found in labeled_mask from bin_img - completed_mask[y, x] = total_pts_num + j - list_labels.append(str(id)+"_"+names+"_unrecovered") - # Put unrecovered coords into new class - self.coords[str(names)+"_unrecovered"] = unrec_points - # Overwrite attribute, only coords that have corresponding objects in the completed_mask - new_points = [] - for i, (x, y) in enumerate(self.coords[names]): - if i not in unrecovered_ids: - new_points.append((x, y)) - self.coords[names] = new_points - - list_labels.sort() + params.debug = debug _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) - return final_mask, list_labels + return final_mask diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 07d8790..d2a7a7a 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -184,7 +184,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") - corrected_mask, _ = counter.correct_mask(bin_img=allmask) + corrected_mask = counter.correct_mask(bin_img=allmask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(discs) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) From b3876cefc0347bc0c34f22660517843ddf2fa0b8 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 17 Jul 2024 16:00:49 -0500 Subject: [PATCH 059/162] remove whitespace --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 5f3a670..c46b80b 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -222,7 +222,7 @@ def correct_mask(self, bin_img): else: # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) final_mask = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) - + params.debug = debug _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, From 0668fd24b89fee98e4478abebdb8d5b5ae7c12a9 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 10:31:33 -0500 Subject: [PATCH 060/162] move correct_mask documentation to Points match style of Outputs class from the main pcv package, remove outdated stuff about the recover_bin_mask since that logic got removed --- docs/Points.md | 53 +++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 52 insertions(+), 1 deletion(-) diff --git a/docs/Points.md b/docs/Points.md index 48f65da..335470e 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -25,7 +25,7 @@ closest collected point. - **Context:** - Used to define a list of coordinates of interest. - - + - Can be helpful to ground truth counting algorithms, and exported coordinates could be used in other image analysis workflows. - **Example use:** - (pcv.roi.multi) - Shown below (pcv.roi.custom) @@ -45,5 +45,56 @@ roi = pcv.roi.custom(img=img, vertices=marker.coords['default']) ``` +## Methods +### Correct a Mask using Point Annotations + +Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it is possible to interactively click to collect coordinates from an image, then use these coordinate to remove and recover objects from a binary mask. + +**plantcv.annotate.Points.correct_mask**(*bin_img*) + +**returns** corrected_mask + +- **Parameters:** + - bin_img - binary image, filtered mask image with selected objects + +- **Context:** + - Filters objects from the `bin_mask` if they do not overlap with an annotation in the `Points` class instance. Also adds a labeled pixel to the corrected mask if an object cannot be resolved for any annotations. + +- **Example use:** + - Remove noise from a microscopy image that is otherwise difficult to filter out with traditional computer vision + techniques, and recover stomata that were filtered out during mask cleaning. + +**Original Image with Annotations** + +![Screenshot](img/documentation_images/points_correct_mask/annotated_stomata.png) + +**bin_img** + +![Screenshot](img/documentation_images/points_correct_mask/bin_img.png) + +```python +import plantcv.plantcv as pcv +import plantcv.annotate as pcvan + +# Create an instance of the Points class +img, path, name = pcv.readimage("stomata.tif") + +# Segmentation & mask clean up steps here + +# Create an instance of the Points class & click on stomata +marker = pcvan.Points(img=img, figsize=(12,6)) + +corrected_mask = marker.correct_mask(bin_img=mask_clean, bin_img_recover=bin_img_recover) + +debug_vis = pcv.visualize.overlay_two_imgs(img, corrected_mask, alpha=.4) +``` + +**Corrected Mask** + +![Screenshot](img/documentation_images/points_correct_mask/corrected_mask.png) + +**Overlaid Image** + +![Screenshot](img/documentation_images/points_correct_mask/overlay.png) **Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annoate/classes.py) From c8db7d007c9a5acadf04edade4de61d0d6dd8ad6 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 11:22:04 -0500 Subject: [PATCH 061/162] swap out doc images for clearer examples --- .../auto_annotated_stomata.png | Bin 0 -> 139870 bytes .../points_correct_mask/bin_img.png | Bin 16689 -> 0 bytes .../points_correct_mask/bin_img_recover.png | Bin 31507 -> 0 bytes .../points_correct_mask/bin_mask.png | Bin 0 -> 6061 bytes .../colorized_label_img.png | Bin 0 -> 8921 bytes .../points_correct_mask/overlay.png | Bin 150129 -> 0 bytes .../points_correct_mask/shape_img.png | Bin 0 -> 843203 bytes 7 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 docs/img/documentation_images/points_correct_mask/auto_annotated_stomata.png delete mode 100644 docs/img/documentation_images/points_correct_mask/bin_img.png delete mode 100644 docs/img/documentation_images/points_correct_mask/bin_img_recover.png create mode 100644 docs/img/documentation_images/points_correct_mask/bin_mask.png create mode 100644 docs/img/documentation_images/points_correct_mask/colorized_label_img.png delete mode 100644 docs/img/documentation_images/points_correct_mask/overlay.png create mode 100644 docs/img/documentation_images/points_correct_mask/shape_img.png diff --git a/docs/img/documentation_images/points_correct_mask/auto_annotated_stomata.png b/docs/img/documentation_images/points_correct_mask/auto_annotated_stomata.png new file mode 100644 index 0000000000000000000000000000000000000000..1c615235024bc99a596aa95eb5b9767fc2bb9afd GIT binary patch literal 139870 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zev`#hE5rVHWJbIiZd44t94QzGS=xI7*t@?UshtNr-}LV9*V7duf$KU?LToOALMFK# zmB){pGD>uB-m_zuPJyrl-D;PQ_;fmE&bhXznZ@GX-2#UDeZ0mm!`)ikTlx%7%q~tR z?ARnPxx1&dYeZC|7d1TqIe7e?8=0+bOkdu?tynw$v4GGQZV^o!?=gn@A0JLVX)4oH zC}XM`@8X-I5A<#m8qTOYXuHQV6-adOfE{LbMmI!fT`Bo7Nwct* z?ImP3Aig>CvwR0_MdDaQK#{t5`tMqt0N!CgTdGR}}P; zud|w;*me(D9i~lVmOfru?Z{k`U-)+|oUEU=|KOC+JzDM4WV6f@N9JzUp~=x7Fuk$b zE=7bjNnhPzLw#ziZ^! z-6QdjG=7%Rl>)z?dCi$@B7tyHP22&kZI^&0OqwV>$=4EA+{xF?8>9pO)t(Ev|Gx8= zMz8|A6`esF&a$A-ozFN>VJkD<*x*uZqznJSCr`h zqI<`j&NXIQwe5Xt>J73UUPL~m&52a8^eiuNKMzw7l0GhYs~!YeOUOlR6{aY3-1@@~ z19ty0b5nmAU(n$jeYTOiO~+Ppj9d`#D&F5>`6Pdkrz6*z8E$i*cLqmRDeB>Fv*wDq9Tnw&o>E^D@ zL_Q2tBIcO&_f2hy@jmJm-Fcb+rZrgj%)a8mwXnUc0_lnlSf$o-}{w-1{T-O Date: Thu, 18 Jul 2024 14:00:22 -0500 Subject: [PATCH 070/162] show corrected annotations also --- docs/Points.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/Points.md b/docs/Points.md index 23a25cd..2f9ca41 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -94,6 +94,9 @@ colorful = pcv.visualize.colorize_label_img(label_img=corrected_mask) # Analysis steps here size_img = pcv.analyze.size(img=img, labeled_mask=corrected_mask, n_labels=num) ``` +**Annotations post Human Corrections** + +![Screenshot](img/documentation_images/points_correct_mask/annotated_stomata.png) **Corrected (and [Colorized](https://plantcv.readthedocs.io/en/stable/visualize_colorize_label_img/)) Mask** From 1f68361063a7963e5e2f0094cd39f32c628706d0 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 15:15:40 -0500 Subject: [PATCH 071/162] remove extra doc from mkdocs --- mkdocs.yml | 1 - 1 file changed, 1 deletion(-) diff --git a/mkdocs.yml b/mkdocs.yml index 094a717..eff0192 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -22,7 +22,6 @@ nav: - Napari Label: napari_label_classes.md - Napari Open: napari_open.md - Points: Points.md - - Points Correct Mask: points_correct_mask.md - Get Centroids: get_centroids.md markdown_extensions: - toc: From a90adc9f5b8a0af882c9a708906c948a025fce72 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 15:22:44 -0500 Subject: [PATCH 072/162] document method returns --- docs/Points.md | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/docs/Points.md b/docs/Points.md index 2f9ca41..c6d1884 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -57,6 +57,10 @@ Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it - **Parameters:** - bin_img - binary image, filtered mask image with selected objects +- **Returns:** + - corrected_mask - A labeled mask with non-annotated objects filtered out, and unresolvable annotations marked with a single, labeled pixel. + - num - The number of unique objects in the `corrected_mask`. + - **Context:** - Filters objects from the `bin_mask` if they do not overlap with an annotation in the `Points` class instance. Also adds a labeled pixel to the corrected mask if an object cannot be resolved for any annotations. Also returns the number of unique objects in the `corrected_mask` which is useful for downstream analysis. @@ -94,7 +98,7 @@ colorful = pcv.visualize.colorize_label_img(label_img=corrected_mask) # Analysis steps here size_img = pcv.analyze.size(img=img, labeled_mask=corrected_mask, n_labels=num) ``` -**Annotations post Human Corrections** +**Annotations After Human Corrections** ![Screenshot](img/documentation_images/points_correct_mask/annotated_stomata.png) From 26f35719ab7a3e90d069a9e82ea85a2eab2773d9 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 22 Jul 2024 16:12:21 -0500 Subject: [PATCH 073/162] begin adding debug img --- plantcv/annotate/classes.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index ddcd31e..3137753 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -182,8 +182,10 @@ def correct_mask(self, bin_img): labelnames = list(self.count) totalcoor = [] unrecovered_ids = [] - pts_mask = np.zeros(np.shape(bin_img)) - final_mask = np.zeros(np.shape(bin_img)) + pts_mask = np.zeros(np.shape(bin_img), np.uint8) + final_mask = pts_mask.copy() + debug_img = pts_mask.copy() + debug_img = cv2.cvtColor(debug_img, cv2.COLOR_GRAY2RGB) for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -203,6 +205,7 @@ def correct_mask(self, bin_img): for i in range(1, total_obj_num + 1): if i not in keep_object_ids: labeled_mask1[np.where(labeled_mask == i)] = 0 + debug_img[np.where(labeled_mask == i)] = (50,50,50) # Create new binary mask after filtering un-annotated objects completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) # Create a new labeled annotation mask to determine number of annotation per object @@ -227,6 +230,9 @@ def correct_mask(self, bin_img): _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) + _debug(visual=debug_img, + filename=os.path.join(params.debug_outdir, + f"{params.device}_annotation-corrected-debug.png")) # Count the number of objects in the final mask num = len(np.unique(final_mask)) From be02d7f54dfaeee62361d6d7d5ea12fd44725de6 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 23 Jul 2024 09:58:56 -0500 Subject: [PATCH 074/162] return debug img for now --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 3137753..a0137ef 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -236,4 +236,4 @@ def correct_mask(self, bin_img): # Count the number of objects in the final mask num = len(np.unique(final_mask)) - return final_mask, num + return final_mask, num, debug_img From 1a3e80f9126fe2b28b6dea1c8a172e150016b775 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 23 Jul 2024 13:58:03 -0500 Subject: [PATCH 075/162] add ID labels at the end instead and draw contours onto debug img --- plantcv/annotate/classes.py | 18 +++++++++++++++++- 1 file changed, 17 insertions(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index a0137ef..caf6353 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -176,12 +176,16 @@ def correct_mask(self, bin_img): final_mask : numpy.ndarray corrected and labeled mask with recovered and removed objects """ + from plantcv.plantcv import color_palette + debug = params.debug params.debug = None labelnames = list(self.count) totalcoor = [] unrecovered_ids = [] + debug_coords = [] + debug_labels = [] pts_mask = np.zeros(np.shape(bin_img), np.uint8) final_mask = pts_mask.copy() debug_img = pts_mask.copy() @@ -200,6 +204,8 @@ def correct_mask(self, bin_img): # Objects that overlap with one or more annotations get kept masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') keep_object_ids = np.unique(masked_image) + # Create a color scale, use a previously stored scale if available + rand_color = color_palette(num=len(keep_object_ids), saved=True) # Fill in objects that are not overlapping with an annotation for i in range(1, total_obj_num + 1): @@ -217,15 +223,25 @@ def correct_mask(self, bin_img): x = int(x) y = int(y) mask_pixel_value = labeled_mask_all[y, x] + text = f"ID:{i}" + + debug_coords.append(tuple([x,y])) + debug_labels.append(text) + if mask_pixel_value == 0: print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) # Add a pixel where unresolved annotation to the mask final_mask = cv2.circle(final_mask, (x, y), radius=0, color=(i), thickness=-1) + # Add a thicker pixel where unresolved annotation to the debug img + debug_img = cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(i), thickness=-1) else: # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) final_mask = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) - + debug_img = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) + for id, id_label in enumerate(debug_labels): + cv2.putText(img=debug_img, text=id_label, org=debug_coords[id], fontFace=cv2.FONT_HERSHEY_SIMPLEX, + fontScale=params.text_size, color=(150, 150, 150), thickness=params.text_thickness) params.debug = debug _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, From d890e3c453ba1c15fe83eae4a148dbca814f67ad Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 23 Jul 2024 14:19:28 -0500 Subject: [PATCH 076/162] rearrange debug steps, add removed shadows pre colorize --- plantcv/annotate/classes.py | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index caf6353..39e6c8a 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -176,7 +176,7 @@ def correct_mask(self, bin_img): final_mask : numpy.ndarray corrected and labeled mask with recovered and removed objects """ - from plantcv.plantcv import color_palette + from plantcv.plantcv.visualize import colorize_label_img debug = params.debug params.debug = None @@ -189,8 +189,10 @@ def correct_mask(self, bin_img): pts_mask = np.zeros(np.shape(bin_img), np.uint8) final_mask = pts_mask.copy() debug_img = pts_mask.copy() + debug_img = cv2.cvtColor(debug_img, cv2.COLOR_GRAY2RGB) - + debug_img_removed = debug_img.copy() + for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): x = int(x) @@ -204,14 +206,12 @@ def correct_mask(self, bin_img): # Objects that overlap with one or more annotations get kept masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') keep_object_ids = np.unique(masked_image) - # Create a color scale, use a previously stored scale if available - rand_color = color_palette(num=len(keep_object_ids), saved=True) # Fill in objects that are not overlapping with an annotation for i in range(1, total_obj_num + 1): if i not in keep_object_ids: labeled_mask1[np.where(labeled_mask == i)] = 0 - debug_img[np.where(labeled_mask == i)] = (50,50,50) + debug_img_removed[np.where(labeled_mask == i)] = (50,50,50) # Create new binary mask after filtering un-annotated objects completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) # Create a new labeled annotation mask to determine number of annotation per object @@ -239,6 +239,9 @@ def correct_mask(self, bin_img): # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) final_mask = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) debug_img = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) + + debug_img = colorize_label_img(debug_img) + debug_img = debug_img + debug_img_removed for id, id_label in enumerate(debug_labels): cv2.putText(img=debug_img, text=id_label, org=debug_coords[id], fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=params.text_size, color=(150, 150, 150), thickness=params.text_thickness) From e3eec479e15b3e2e78aacd29e77dc6889de50c0c Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 23 Jul 2024 14:46:25 -0500 Subject: [PATCH 077/162] Update classes.py --- plantcv/annotate/classes.py | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 39e6c8a..5cace47 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -218,7 +218,9 @@ def correct_mask(self, bin_img): labeled_mask_all, _ = create_labels(mask=completed_mask_bin) # points in class used for recovering and labeling + multiplier = 0 for names in labelnames: + multiplier =+1 for i, (x, y) in enumerate(self.coords[names]): x = int(x) y = int(y) @@ -232,13 +234,13 @@ def correct_mask(self, bin_img): print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) # Add a pixel where unresolved annotation to the mask - final_mask = cv2.circle(final_mask, (x, y), radius=0, color=(i), thickness=-1) + final_mask = cv2.circle(final_mask, (x, y), radius=0, color=i+1, thickness=-1) # Add a thicker pixel where unresolved annotation to the debug img - debug_img = cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(i), thickness=-1) + debug_img = cv2.circle(debug_img, (x, y), radius=int(params.line_thickness), color=i+1, thickness=-1) else: # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) - final_mask = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) - debug_img = np.where(labeled_mask_all == mask_pixel_value, i, final_mask) + final_mask = np.where(labeled_mask_all == mask_pixel_value, i+1, final_mask) + debug_img = np.where(labeled_mask_all == mask_pixel_value, i+1, final_mask) debug_img = colorize_label_img(debug_img) debug_img = debug_img + debug_img_removed From 73485fb828fc0a1df5208498bb4d6a35bc5af51a Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 23 Jul 2024 15:23:42 -0500 Subject: [PATCH 078/162] i+1 so skipping 0 pixel not plotted --- plantcv/annotate/classes.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 5cace47..dac5a15 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -218,9 +218,7 @@ def correct_mask(self, bin_img): labeled_mask_all, _ = create_labels(mask=completed_mask_bin) # points in class used for recovering and labeling - multiplier = 0 for names in labelnames: - multiplier =+1 for i, (x, y) in enumerate(self.coords[names]): x = int(x) y = int(y) @@ -234,9 +232,10 @@ def correct_mask(self, bin_img): print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) # Add a pixel where unresolved annotation to the mask - final_mask = cv2.circle(final_mask, (x, y), radius=0, color=i+1, thickness=-1) + final_mask = cv2.circle(final_mask, (x, y), radius=0, color=(i+1), thickness=-1) # Add a thicker pixel where unresolved annotation to the debug img - debug_img = cv2.circle(debug_img, (x, y), radius=int(params.line_thickness), color=i+1, thickness=-1) + j = i+1 + debug_img = cv2.circle(debug_img, (x, y), params.line_thickness, color=(j, j, j), thickness=2) else: # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) final_mask = np.where(labeled_mask_all == mask_pixel_value, i+1, final_mask) From 644f3433fc590145b6a2bb2e4b484d16ad19dbf1 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 25 Jul 2024 13:59:59 -0500 Subject: [PATCH 079/162] unresolved debug thickness bug RESOLVED --- plantcv/annotate/classes.py | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index dac5a15..1d78837 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -189,9 +189,8 @@ def correct_mask(self, bin_img): pts_mask = np.zeros(np.shape(bin_img), np.uint8) final_mask = pts_mask.copy() debug_img = pts_mask.copy() - - debug_img = cv2.cvtColor(debug_img, cv2.COLOR_GRAY2RGB) - debug_img_removed = debug_img.copy() + debug_img_removed = pts_mask.copy() + debug_img_removed = cv2.cvtColor(debug_img_removed, cv2.COLOR_GRAY2RGB) for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -223,7 +222,7 @@ def correct_mask(self, bin_img): x = int(x) y = int(y) mask_pixel_value = labeled_mask_all[y, x] - text = f"ID:{i}" + text = f"ID:{i+1}" debug_coords.append(tuple([x,y])) debug_labels.append(text) @@ -234,12 +233,11 @@ def correct_mask(self, bin_img): # Add a pixel where unresolved annotation to the mask final_mask = cv2.circle(final_mask, (x, y), radius=0, color=(i+1), thickness=-1) # Add a thicker pixel where unresolved annotation to the debug img - j = i+1 - debug_img = cv2.circle(debug_img, (x, y), params.line_thickness, color=(j, j, j), thickness=2) + debug_img = cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(i+1), thickness=-1) else: # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) final_mask = np.where(labeled_mask_all == mask_pixel_value, i+1, final_mask) - debug_img = np.where(labeled_mask_all == mask_pixel_value, i+1, final_mask) + debug_img = np.where(labeled_mask_all == mask_pixel_value, i+1, debug_img) debug_img = colorize_label_img(debug_img) debug_img = debug_img + debug_img_removed From 96ff8a81d6ad79e478214e6b1f30c64edf6692f4 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 25 Jul 2024 14:11:32 -0500 Subject: [PATCH 080/162] quit returning debug image --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 1d78837..4bc92af 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -254,4 +254,4 @@ def correct_mask(self, bin_img): # Count the number of objects in the final mask num = len(np.unique(final_mask)) - return final_mask, num, debug_img + return final_mask, num From 99d2282b0c214bf9ffacad218ec5005565ff090a Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 26 Jul 2024 09:43:47 -0500 Subject: [PATCH 081/162] remove "id" part of text label --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 4bc92af..e5aaf46 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -222,7 +222,7 @@ def correct_mask(self, bin_img): x = int(x) y = int(y) mask_pixel_value = labeled_mask_all[y, x] - text = f"ID:{i+1}" + text = str(i+1) debug_coords.append(tuple([x,y])) debug_labels.append(text) From af86fcc3f4f1fe09f78b43f2b4add28a65f07917 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 29 Jul 2024 10:28:43 -0500 Subject: [PATCH 082/162] update docstrings for correct-mask function --- plantcv/annotate/classes.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index e5aaf46..01599e9 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -164,17 +164,19 @@ class label, by default "default" self.ax.plot(x, y, marker='x', c=self.color) def correct_mask(self, bin_img): - """View coordinates for a specific class label. + """Fitler a binary mask and make a labeled mask for analysis. Parameters ---------- bin_img : numpy.ndarray - binary image, filtered mask image with selected objects + binary image, mask to get corrected Returns ---------- final_mask : numpy.ndarray corrected and labeled mask with recovered and removed objects + num : int + number of objects represented within the labeled mask """ from plantcv.plantcv.visualize import colorize_label_img From a49b9bf9673406d126f290880c3977596b9f06ef Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 29 Jul 2024 10:33:07 -0500 Subject: [PATCH 083/162] split up context documentation and clarify --- docs/Points.md | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/docs/Points.md b/docs/Points.md index c6d1884..89e6bcc 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -36,7 +36,7 @@ import plantcv.plantcv as pcv import plantcv.annotate as an # Create an instance of the Points class -marker = an.Points(img=img, figsize=(12,6)) +marker = an.Points(img=img, figsize=(12,6), label='default') # Click on the plotted image to collect coordinates @@ -62,7 +62,10 @@ Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it - num - The number of unique objects in the `corrected_mask`. - **Context:** - - Filters objects from the `bin_mask` if they do not overlap with an annotation in the `Points` class instance. Also adds a labeled pixel to the corrected mask if an object cannot be resolved for any annotations. Also returns the number of unique objects in the `corrected_mask` which is useful for downstream analysis. + - Filters objects from the `bin_mask` if they do not overlap with an annotation in the `Points` class instance. + - Adds a labeled pixel to the corrected mask if an object cannot be resolved for any annotations (false negatives can be counted but cannot have their size measured downstream). + - Returns the number of unique objects in the `corrected_mask` which is useful for downstream analysis. + - Debug image is a colorized representation of the labeled mask. The "unresolved" annotation replicates are plotted with a radius of `pcv.params.line_thickness` (default = 5). - **Example use:** - Remove noise from a microscopy image that is otherwise difficult to filter out with traditional computer vision From dd14d7d0922e2f05e145953a70bdca98da53979b Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 29 Jul 2024 10:35:14 -0500 Subject: [PATCH 084/162] replace doc images with new debug --- .../points_correct_mask/annotated_stomata.png | Bin 138104 -> 138877 bytes .../colorized_label_img.png | Bin 31396 -> 43415 bytes 2 files changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/img/documentation_images/points_correct_mask/annotated_stomata.png b/docs/img/documentation_images/points_correct_mask/annotated_stomata.png index e6f53776b80ba309ff2d6a40de91fee270c3f899..56402d0036d6655b8dd90313d13a6447cba1a56e 100644 GIT binary patch delta 127524 zcmc%w`8(AA_XmzYvn0e68QYj?VU#thu{M$|dz*bXibB?Gjd_F+gRvxJ3q_HA$-Xlt 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zH?hiL8MkiNizY{YeTG{a+M~M|SpC9{dfRQVaQ&?_sqbi`zJcdk+KZ*$O*6dzJSqO= zMml_56Dwt7&#;`?n;dgbE^|71t1EBn{8bV7)Bg87h0txKSO1Z|r+~Y_?592nJEUGi z>x;fFjxc#kp~87QtKx;zylrlr4QWK5Smt{fR}sfrbBq{r3K!?$U6!%rg_*zUB{zc2 zEfLSD5%~cTu>Cfor5&S>#@v?5V5nbr(yXfsP%zJcrd+drWu2d1w2&Tyjug6#P4|1! z!wYd(G4oeJ+FXe{Ppm|`>JaI$s`G?E)-(?RtO>W8L@k&9HlS%Rnq#zx$8um-T8nbz zPHg%Ic|Mh9hOaRa&!CrnVL$uK^N3`7P6BW)OU363RUF|G?~&7AB@q|QsHvD8@Z@xU z9EKFZQNaOlZ6bvsS{%(AQc4L*+AC{#CiI4<@^o4E)kB_w> zploe=lDDkaNhWTyp*oj=DHGT*_I-cG9hw()lTFn^p)IQ4x&$Hpin*m$mcFAjc7;o1 zHGBPMwxfd{mq|N1HVAL$Sj_RlhC429+i{ase@Lm-|>nXYD7oz$1|3$A**>g^<A$An(S(h5Rlmv^j4Cf+r7wVzT}f4U>%W%tf$jSFZ3x ze^458SR7&cS;7#;QplVB{*p4W_bXU*PIGOH<@^gVNnoOQUs1inf!2Mf#z*KJ>|{RV zr?$|pEhlhn9q#(_K>DXdEGF80MGc;gNP681T26hMI`Y*B2&N1PQsK~tc5bbF;zpp- z8@xL!n^bg>v}rwv09kR643!Am%HI)6TkA>{^jaxk=FO~ From d2bdce40aa0184efeee949091597eeac35095387 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 29 Jul 2024 10:35:47 -0500 Subject: [PATCH 085/162] remove colorize step from code example debug image already has a colorful image now so not needed --- docs/Points.md | 3 --- 1 file changed, 3 deletions(-) diff --git a/docs/Points.md b/docs/Points.md index 89e6bcc..97fb6a6 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -95,9 +95,6 @@ marker.import_list(coords=centroid_coords, label="stomata") # Filter the binary mask based on corrected annotations corrected_mask, num = marker.correct_mask(bin_img=bin_mask) -# Optional visualization -colorful = pcv.visualize.colorize_label_img(label_img=corrected_mask) - # Analysis steps here size_img = pcv.analyze.size(img=img, labeled_mask=corrected_mask, n_labels=num) ``` From 0f3efb2cdc2b39df929a247ec714e632bae4f145 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 29 Jul 2024 10:46:37 -0500 Subject: [PATCH 086/162] deepsource fixes and minor comment updates in correct_mask --- plantcv/annotate/classes.py | 17 +++++++---------- 1 file changed, 7 insertions(+), 10 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 01599e9..2b3cdc3 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -182,7 +182,6 @@ def correct_mask(self, bin_img): debug = params.debug params.debug = None - labelnames = list(self.count) totalcoor = [] unrecovered_ids = [] @@ -193,7 +192,7 @@ def correct_mask(self, bin_img): debug_img = pts_mask.copy() debug_img_removed = pts_mask.copy() debug_img_removed = cv2.cvtColor(debug_img_removed, cv2.COLOR_GRAY2RGB) - + for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): x = int(x) @@ -212,23 +211,21 @@ def correct_mask(self, bin_img): for i in range(1, total_obj_num + 1): if i not in keep_object_ids: labeled_mask1[np.where(labeled_mask == i)] = 0 - debug_img_removed[np.where(labeled_mask == i)] = (50,50,50) + debug_img_removed[np.where(labeled_mask == i)] = (50, 50, 50) # Create new binary mask after filtering un-annotated objects completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) # Create a new labeled annotation mask to determine number of annotation per object labeled_mask_all, _ = create_labels(mask=completed_mask_bin) - - # points in class used for recovering and labeling + # pts in class used for recovering and labeling for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): x = int(x) y = int(y) mask_pixel_value = labeled_mask_all[y, x] text = str(i+1) - - debug_coords.append(tuple([x,y])) + debug_coords.append((x, y)) debug_labels.append(text) - + # Check if current annotation can be resolved to an object in the mask if mask_pixel_value == 0: print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) @@ -237,10 +234,10 @@ def correct_mask(self, bin_img): # Add a thicker pixel where unresolved annotation to the debug img debug_img = cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(i+1), thickness=-1) else: - # DRAW on labeled mask with correct pixel value (object ID and np.where to copy with new label ID i) + # Draw on labeled mask with correct pixel value final_mask = np.where(labeled_mask_all == mask_pixel_value, i+1, final_mask) debug_img = np.where(labeled_mask_all == mask_pixel_value, i+1, debug_img) - + debug_img = colorize_label_img(debug_img) debug_img = debug_img + debug_img_removed for id, id_label in enumerate(debug_labels): From 031de7097932e54ebdf6b2fda3f027d4f4caa1f4 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 29 Jul 2024 13:17:31 -0500 Subject: [PATCH 087/162] update labeled mask datatype to uint32 --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 2b3cdc3..d41c463 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -188,7 +188,7 @@ def correct_mask(self, bin_img): debug_coords = [] debug_labels = [] pts_mask = np.zeros(np.shape(bin_img), np.uint8) - final_mask = pts_mask.copy() + final_mask = pts_mask.copy().astype(np.uint32) debug_img = pts_mask.copy() debug_img_removed = pts_mask.copy() debug_img_removed = cv2.cvtColor(debug_img_removed, cv2.COLOR_GRAY2RGB) From 60eb08657be6f1eea1aeb0114b88e0b111cedbfb Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 09:13:10 -0500 Subject: [PATCH 088/162] update method of drawing on final mask, add object count logic rather than using i in the double for loop, fir rep of each group is same label no good, change to a counter for total objects --- plantcv/annotate/classes.py | 13 +++++++++---- 1 file changed, 9 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index d41c463..4e10ca5 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -216,6 +216,8 @@ def correct_mask(self, bin_img): completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) # Create a new labeled annotation mask to determine number of annotation per object labeled_mask_all, _ = create_labels(mask=completed_mask_bin) + # Initialize object count + object_id_count = 1 # pts in class used for recovering and labeling for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -230,13 +232,16 @@ def correct_mask(self, bin_img): print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) # Add a pixel where unresolved annotation to the mask - final_mask = cv2.circle(final_mask, (x, y), radius=0, color=(i+1), thickness=-1) + # final_mask = cv2.circle(final_mask, (x, y), radius=0, + # color=(object_id_count), thickness=-1) + cv2.drawContours(final_mask, [(x, y)], -1, (object_id_count), -1) # Add a thicker pixel where unresolved annotation to the debug img - debug_img = cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(i+1), thickness=-1) + cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) else: # Draw on labeled mask with correct pixel value - final_mask = np.where(labeled_mask_all == mask_pixel_value, i+1, final_mask) - debug_img = np.where(labeled_mask_all == mask_pixel_value, i+1, debug_img) + final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) + debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) + object_id_count += 1 debug_img = colorize_label_img(debug_img) debug_img = debug_img + debug_img_removed From bf4f0b55c0d54621a409e5582927f406905ec49e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 09:58:21 -0500 Subject: [PATCH 089/162] datatype BUGFIX drawCountours doesn't play nice with uint32 so change method for drawing unresolved pixels on the labeled mask --- plantcv/annotate/classes.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 4e10ca5..6ecb1cc 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -229,12 +229,10 @@ def correct_mask(self, bin_img): debug_labels.append(text) # Check if current annotation can be resolved to an object in the mask if mask_pixel_value == 0: - print(f"Un-Recoverable object at coordinate: x = {x}, y = {y}") + print(f"Object could not be resolved at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) # Add a pixel where unresolved annotation to the mask - # final_mask = cv2.circle(final_mask, (x, y), radius=0, - # color=(object_id_count), thickness=-1) - cv2.drawContours(final_mask, [(x, y)], -1, (object_id_count), -1) + final_mask[y,x] = object_id_count # Add a thicker pixel where unresolved annotation to the debug img cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) else: @@ -243,8 +241,10 @@ def correct_mask(self, bin_img): debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) object_id_count += 1 + # Combine and colorize the debug image debug_img = colorize_label_img(debug_img) debug_img = debug_img + debug_img_removed + # Write ID labels for id, id_label in enumerate(debug_labels): cv2.putText(img=debug_img, text=id_label, org=debug_coords[id], fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=params.text_size, color=(150, 150, 150), thickness=params.text_thickness) From f95b5f6fe47a978704704af140f8d74229577732 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 10:01:19 -0500 Subject: [PATCH 090/162] nest warning statement in verbose "if" possible to have hundreds of unresolved things so want to have the option to turn this off --- plantcv/annotate/classes.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 6ecb1cc..3754ad6 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -229,7 +229,8 @@ def correct_mask(self, bin_img): debug_labels.append(text) # Check if current annotation can be resolved to an object in the mask if mask_pixel_value == 0: - print(f"Object could not be resolved at coordinate: x = {x}, y = {y}") + if params.verbose == True: + print(f"Object could not be resolved at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) # Add a pixel where unresolved annotation to the mask final_mask[y,x] = object_id_count From b88436451d1f894b66e69b59b45b161660aac288 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 10:25:57 -0500 Subject: [PATCH 091/162] update text ID labels --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 3754ad6..3fe297b 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -224,7 +224,7 @@ def correct_mask(self, bin_img): x = int(x) y = int(y) mask_pixel_value = labeled_mask_all[y, x] - text = str(i+1) + text = str(object_id_count) debug_coords.append((x, y)) debug_labels.append(text) # Check if current annotation can be resolved to an object in the mask From 8cbd37359662bcbf2492732a0d0a53cce0047f6f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 12:06:21 -0500 Subject: [PATCH 092/162] double annotated obj handling start not good yet --- plantcv/annotate/classes.py | 17 +++++++++++++---- 1 file changed, 13 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 3fe297b..70c6e57 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -187,6 +187,7 @@ def correct_mask(self, bin_img): unrecovered_ids = [] debug_coords = [] debug_labels = [] + added_obj_labels = [] pts_mask = np.zeros(np.shape(bin_img), np.uint8) final_mask = pts_mask.copy().astype(np.uint32) debug_img = pts_mask.copy() @@ -236,10 +237,18 @@ def correct_mask(self, bin_img): final_mask[y,x] = object_id_count # Add a thicker pixel where unresolved annotation to the debug img cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) - else: - # Draw on labeled mask with correct pixel value - final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) - debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) + if mask_pixel_value > 0: + if mask_pixel_value not in added_obj_labels: + # New object getting added + added_obj_labels.append(mask_pixel_value) + # Draw on labeled mask with correct pixel value + final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) + debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) + else: + # Determine label duplicate or unique for combination + class_labels_list = [k for k, v in self.coords.items() if v == (x,y)] + print(class_labels_list) + object_id_count += 1 # Combine and colorize the debug image From 962be3812c9f73540c61a328ee19e7604e0d4fb7 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 13:35:58 -0500 Subject: [PATCH 093/162] adding label list and combining unique labels --- plantcv/annotate/classes.py | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 70c6e57..5e8a6cb 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -188,6 +188,7 @@ def correct_mask(self, bin_img): debug_coords = [] debug_labels = [] added_obj_labels = [] + added_obj_classes = [] pts_mask = np.zeros(np.shape(bin_img), np.uint8) final_mask = pts_mask.copy().astype(np.uint32) debug_img = pts_mask.copy() @@ -241,13 +242,20 @@ def correct_mask(self, bin_img): if mask_pixel_value not in added_obj_labels: # New object getting added added_obj_labels.append(mask_pixel_value) + added_obj_classes.append(names) # Draw on labeled mask with correct pixel value final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) else: + original_label = added_obj_classes[added_obj_labels.index(mask_pixel_value)] # Determine label duplicate or unique for combination - class_labels_list = [k for k, v in self.coords.items() if v == (x,y)] - print(class_labels_list) + coord_class_label = [k for k, v in self.coords.items() if (x, y) in v] + if original_label == coord_class_label: + # We found a duplicate so skip ????? + pass + else: + # Combine labels + added_obj_classes[added_obj_labels.index(mask_pixel_value)] = original_label + "_" + coord_class_label[0] object_id_count += 1 @@ -267,5 +275,6 @@ def correct_mask(self, bin_img): f"{params.device}_annotation-corrected-debug.png")) # Count the number of objects in the final mask num = len(np.unique(final_mask)) + print(added_obj_classes) return final_mask, num From ea81d26e4a6456bee6452d5bc4d61dc1866fae06 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 16:21:47 -0500 Subject: [PATCH 094/162] return analysis_labels and append in unresolved case too --- plantcv/annotate/classes.py | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 5e8a6cb..198810c 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -188,7 +188,7 @@ def correct_mask(self, bin_img): debug_coords = [] debug_labels = [] added_obj_labels = [] - added_obj_classes = [] + analysis_labels = [] pts_mask = np.zeros(np.shape(bin_img), np.uint8) final_mask = pts_mask.copy().astype(np.uint32) debug_img = pts_mask.copy() @@ -234,6 +234,8 @@ def correct_mask(self, bin_img): if params.verbose == True: print(f"Object could not be resolved at coordinate: x = {x}, y = {y}") unrecovered_ids.append(i) + added_obj_labels.append(mask_pixel_value) + analysis_labels.append(names) # Add a pixel where unresolved annotation to the mask final_mask[y,x] = object_id_count # Add a thicker pixel where unresolved annotation to the debug img @@ -242,20 +244,21 @@ def correct_mask(self, bin_img): if mask_pixel_value not in added_obj_labels: # New object getting added added_obj_labels.append(mask_pixel_value) - added_obj_classes.append(names) + analysis_labels.append(names) # Draw on labeled mask with correct pixel value final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) else: - original_label = added_obj_classes[added_obj_labels.index(mask_pixel_value)] + original_label = analysis_labels[added_obj_labels.index(mask_pixel_value)] # Determine label duplicate or unique for combination coord_class_label = [k for k, v in self.coords.items() if (x, y) in v] - if original_label == coord_class_label: + if original_label == coord_class_label[0]: # We found a duplicate so skip ????? + debug_img = np.where(labeled_mask_all == mask_pixel_value, 0.5, debug_img) pass else: # Combine labels - added_obj_classes[added_obj_labels.index(mask_pixel_value)] = original_label + "_" + coord_class_label[0] + analysis_labels[added_obj_labels.index(mask_pixel_value)] = original_label + "_" + coord_class_label[0] object_id_count += 1 @@ -275,6 +278,5 @@ def correct_mask(self, bin_img): f"{params.device}_annotation-corrected-debug.png")) # Count the number of objects in the final mask num = len(np.unique(final_mask)) - print(added_obj_classes) - return final_mask, num + return final_mask, analysis_labels, num From a94be11ca42e1e98c487517861a92e9b45bd25bd Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 16:22:05 -0500 Subject: [PATCH 095/162] num -1 since background --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 198810c..0f7ea9d 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -277,6 +277,6 @@ def correct_mask(self, bin_img): filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected-debug.png")) # Count the number of objects in the final mask - num = len(np.unique(final_mask)) + num = len(np.unique(final_mask)) - 1 return final_mask, analysis_labels, num From 8f3324cdc984002845491f2b9ecb320f07473d21 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 16:33:32 -0500 Subject: [PATCH 096/162] update duplication for clumps greater than 2 --- plantcv/annotate/classes.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 0f7ea9d..15774d8 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -249,10 +249,11 @@ def correct_mask(self, bin_img): final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) else: + # Object annotated more than once so find original object label original_label = analysis_labels[added_obj_labels.index(mask_pixel_value)] # Determine label duplicate or unique for combination coord_class_label = [k for k, v in self.coords.items() if (x, y) in v] - if original_label == coord_class_label[0]: + if coord_class_label[0] in original_label: # We found a duplicate so skip ????? debug_img = np.where(labeled_mask_all == mask_pixel_value, 0.5, debug_img) pass From 309840bdc8c3a0759a96e8408215ded7a0fab1b0 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 31 Jul 2024 16:58:38 -0500 Subject: [PATCH 097/162] change duplicate annotated debug objs --- plantcv/annotate/classes.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 15774d8..0ef53f3 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -179,6 +179,7 @@ def correct_mask(self, bin_img): number of objects represented within the labeled mask """ from plantcv.plantcv.visualize import colorize_label_img + from plantcv.plantcv import dilate debug = params.debug params.debug = None @@ -194,6 +195,7 @@ def correct_mask(self, bin_img): debug_img = pts_mask.copy() debug_img_removed = pts_mask.copy() debug_img_removed = cv2.cvtColor(debug_img_removed, cv2.COLOR_GRAY2RGB) + debug_img_duplicates = debug_img_removed.copy() for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -255,7 +257,7 @@ def correct_mask(self, bin_img): coord_class_label = [k for k, v in self.coords.items() if (x, y) in v] if coord_class_label[0] in original_label: # We found a duplicate so skip ????? - debug_img = np.where(labeled_mask_all == mask_pixel_value, 0.5, debug_img) + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img) pass else: # Combine labels @@ -264,8 +266,10 @@ def correct_mask(self, bin_img): object_id_count += 1 # Combine and colorize the debug image + debug_img_duplicates = dilate(debug_img_duplicates, ksize=params.line_thickness, i=1) + debug_img_duplicates = cv2.cvtColor(debug_img_duplicates, cv2.COLOR_GRAY2RGB) debug_img = colorize_label_img(debug_img) - debug_img = debug_img + debug_img_removed + debug_img = debug_img + debug_img_removed + debug_img_duplicates # Write ID labels for id, id_label in enumerate(debug_labels): cv2.putText(img=debug_img, text=id_label, org=debug_coords[id], fontFace=cv2.FONT_HERSHEY_SIMPLEX, From 7457c7aeffb82a921ef4d59ab7b02d1ec783638b Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 1 Aug 2024 10:26:06 -0500 Subject: [PATCH 098/162] remove duplicated things and replace with coord --- plantcv/annotate/classes.py | 35 ++++++++++++++++++++++++++++------- 1 file changed, 28 insertions(+), 7 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 0ef53f3..9872371 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -195,7 +195,7 @@ def correct_mask(self, bin_img): debug_img = pts_mask.copy() debug_img_removed = pts_mask.copy() debug_img_removed = cv2.cvtColor(debug_img_removed, cv2.COLOR_GRAY2RGB) - debug_img_duplicates = debug_img_removed.copy() + debug_img_duplicates = pts_mask.copy() for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -216,6 +216,14 @@ def correct_mask(self, bin_img): if i not in keep_object_ids: labeled_mask1[np.where(labeled_mask == i)] = 0 debug_img_removed[np.where(labeled_mask == i)] = (50, 50, 50) + # # Check if annotation is unique + # if counts[i] > 1: + # # Remove the object + # labeled_mask1[np.where(labeled_mask == i)] = 0 + # # Draw a pixel at each of the annotation + # labeled_mask1 = np.where(masked_image == i, (255), labeled_mask1) + # # Removed object drawn on debug image + # debug_img_removed[np.where(labeled_mask == i)] = (100, 100, 100) # Create new binary mask after filtering un-annotated objects completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) # Create a new labeled annotation mask to determine number of annotation per object @@ -243,6 +251,7 @@ def correct_mask(self, bin_img): # Add a thicker pixel where unresolved annotation to the debug img cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) if mask_pixel_value > 0: + # An object is resolved but check if it's already been annotated if mask_pixel_value not in added_obj_labels: # New object getting added added_obj_labels.append(mask_pixel_value) @@ -252,21 +261,33 @@ def correct_mask(self, bin_img): debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) else: # Object annotated more than once so find original object label - original_label = analysis_labels[added_obj_labels.index(mask_pixel_value)] + original_index = added_obj_labels.index(mask_pixel_value) + original_label = analysis_labels[original_index] + original_coord = debug_coords[original_index] # Determine label duplicate or unique for combination coord_class_label = [k for k, v in self.coords.items() if (x, y) in v] if coord_class_label[0] in original_label: - # We found a duplicate so skip ????? - debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img) - pass + # We found a duplicate + debug_img = np.where(labeled_mask_all == mask_pixel_value, (0), debug_img) + cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) + cv2.circle(debug_img, original_coord, radius=params.line_thickness, color=(original_index), thickness=-1) + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + # Fill in the duplicate object in the labeled mask, replace with pixel annotations + final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) + final_mask[y,x] = object_id_count + final_mask[original_coord[1], original_coord[0]] = original_index else: - # Combine labels + # If unique then combine labels analysis_labels[added_obj_labels.index(mask_pixel_value)] = original_label + "_" + coord_class_label[0] + # De-increment object count since just a single object + object_id_count -= 1 object_id_count += 1 # Combine and colorize the debug image - debug_img_duplicates = dilate(debug_img_duplicates, ksize=params.line_thickness, i=1) + # Dilate duplicate objs and subtract the object itself to leave just a halo around + debug_img_duplicates1 = dilate(debug_img_duplicates, ksize=params.line_thickness, i=1) + debug_img_duplicates = debug_img_duplicates1 - debug_img_duplicates debug_img_duplicates = cv2.cvtColor(debug_img_duplicates, cv2.COLOR_GRAY2RGB) debug_img = colorize_label_img(debug_img) debug_img = debug_img + debug_img_removed + debug_img_duplicates From 494939059218debd5a0ea932ea978b99350f1e06 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 1 Aug 2024 10:36:35 -0500 Subject: [PATCH 099/162] change where ID labels are getting added dont add labels in cases where duplicate but unique objects --- plantcv/annotate/classes.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 9872371..d49427f 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -237,8 +237,7 @@ def correct_mask(self, bin_img): y = int(y) mask_pixel_value = labeled_mask_all[y, x] text = str(object_id_count) - debug_coords.append((x, y)) - debug_labels.append(text) + # Check if current annotation can be resolved to an object in the mask if mask_pixel_value == 0: if params.verbose == True: @@ -250,6 +249,9 @@ def correct_mask(self, bin_img): final_mask[y,x] = object_id_count # Add a thicker pixel where unresolved annotation to the debug img cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) + # Add debug label annotations later + debug_coords.append((x, y)) + debug_labels.append(text) if mask_pixel_value > 0: # An object is resolved but check if it's already been annotated if mask_pixel_value not in added_obj_labels: @@ -259,6 +261,9 @@ def correct_mask(self, bin_img): # Draw on labeled mask with correct pixel value final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) + # Add debug label annotations later + debug_coords.append((x, y)) + debug_labels.append(text) else: # Object annotated more than once so find original object label original_index = added_obj_labels.index(mask_pixel_value) From 5462ce19182dcdae9027e68ef7aebd84fa46d59f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 1 Aug 2024 12:19:19 -0500 Subject: [PATCH 100/162] almost one to one objects and labels --- plantcv/annotate/classes.py | 19 ++++++++++++++----- 1 file changed, 14 insertions(+), 5 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index d49427f..3be5c70 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -242,8 +242,8 @@ def correct_mask(self, bin_img): if mask_pixel_value == 0: if params.verbose == True: print(f"Object could not be resolved at coordinate: x = {x}, y = {y}") - unrecovered_ids.append(i) - added_obj_labels.append(mask_pixel_value) + unrecovered_ids.append(object_id_count) + added_obj_labels.append(object_id_count) analysis_labels.append(names) # Add a pixel where unresolved annotation to the mask final_mask[y,x] = object_id_count @@ -272,15 +272,24 @@ def correct_mask(self, bin_img): # Determine label duplicate or unique for combination coord_class_label = [k for k, v in self.coords.items() if (x, y) in v] if coord_class_label[0] in original_label: - # We found a duplicate - debug_img = np.where(labeled_mask_all == mask_pixel_value, (0), debug_img) + # We found a duplicate label + # New object getting added + added_obj_labels.append(object_id_count) + analysis_labels.append(names) + # Fill in the duplicate object in the debug mask + debug_img = np.where(debug_img == mask_pixel_value, (0), debug_img) + # Replace with pixel annotations in debug cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) cv2.circle(debug_img, original_coord, radius=params.line_thickness, color=(original_index), thickness=-1) + # Draw the ghost of objects removed debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + # Add debug label annotations later + debug_coords.append((x, y)) + debug_labels.append(text) # Fill in the duplicate object in the labeled mask, replace with pixel annotations final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) final_mask[y,x] = object_id_count - final_mask[original_coord[1], original_coord[0]] = original_index + final_mask[original_coord[1], original_coord[0]] = original_index + 1 else: # If unique then combine labels analysis_labels[added_obj_labels.index(mask_pixel_value)] = original_label + "_" + coord_class_label[0] From 13a440cf04199ebd55e8e6d6cd3a4cb38baad15f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 2 Aug 2024 14:37:47 -0500 Subject: [PATCH 101/162] comment out labeled mask plot --- plantcv/annotate/classes.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 3be5c70..ba127a0 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -277,7 +277,7 @@ def correct_mask(self, bin_img): added_obj_labels.append(object_id_count) analysis_labels.append(names) # Fill in the duplicate object in the debug mask - debug_img = np.where(debug_img == mask_pixel_value, (0), debug_img) + debug_img = np.where(debug_img == original_index, (0), debug_img) # Replace with pixel annotations in debug cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) cv2.circle(debug_img, original_coord, radius=params.line_thickness, color=(original_index), thickness=-1) @@ -310,9 +310,9 @@ def correct_mask(self, bin_img): cv2.putText(img=debug_img, text=id_label, org=debug_coords[id], fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=params.text_size, color=(150, 150, 150), thickness=params.text_thickness) params.debug = debug - _debug(visual=final_mask, - filename=os.path.join(params.debug_outdir, - f"{params.device}_annotation-corrected.png")) + # _debug(visual=final_mask, + # filename=os.path.join(params.debug_outdir, + # f"{params.device}_annotation-corrected.png")) _debug(visual=debug_img, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected-debug.png")) From 6933dde692c17e2d9fc692ff5d2c17660afa86b8 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 2 Aug 2024 14:45:23 -0500 Subject: [PATCH 102/162] remove commented code, and check for annotation count --- plantcv/annotate/classes.py | 15 +++++---------- 1 file changed, 5 insertions(+), 10 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index ba127a0..4f1ff14 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -216,18 +216,12 @@ def correct_mask(self, bin_img): if i not in keep_object_ids: labeled_mask1[np.where(labeled_mask == i)] = 0 debug_img_removed[np.where(labeled_mask == i)] = (50, 50, 50) - # # Check if annotation is unique - # if counts[i] > 1: - # # Remove the object - # labeled_mask1[np.where(labeled_mask == i)] = 0 - # # Draw a pixel at each of the annotation - # labeled_mask1 = np.where(masked_image == i, (255), labeled_mask1) - # # Removed object drawn on debug image - # debug_img_removed[np.where(labeled_mask == i)] = (100, 100, 100) # Create new binary mask after filtering un-annotated objects completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) # Create a new labeled annotation mask to determine number of annotation per object labeled_mask_all, _ = create_labels(mask=completed_mask_bin) + masked_image2 = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') + keep_object_ids, keep_object_count = np.unique(masked_image2, return_counts=True) # Initialize object count object_id_count = 1 # pts in class used for recovering and labeling @@ -254,7 +248,8 @@ def correct_mask(self, bin_img): debug_labels.append(text) if mask_pixel_value > 0: # An object is resolved but check if it's already been annotated - if mask_pixel_value not in added_obj_labels: + resolved_id = keep_object_ids.index(mask_pixel_value) + if keep_object_count[resolved_id] == 1: # New object getting added added_obj_labels.append(mask_pixel_value) analysis_labels.append(names) @@ -264,7 +259,7 @@ def correct_mask(self, bin_img): # Add debug label annotations later debug_coords.append((x, y)) debug_labels.append(text) - else: + if keep_object_count[resolved_id] > 1: # Object annotated more than once so find original object label original_index = added_obj_labels.index(mask_pixel_value) original_label = analysis_labels[original_index] From b331517fadb7a90ad45edffad9292dfb0c94215f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 5 Aug 2024 11:34:00 -0500 Subject: [PATCH 103/162] extract class labels for duplicate annotations --- plantcv/annotate/classes.py | 78 +++++++++++++++++++++---------------- 1 file changed, 45 insertions(+), 33 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 4f1ff14..df17866 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -222,6 +222,8 @@ def correct_mask(self, bin_img): labeled_mask_all, _ = create_labels(mask=completed_mask_bin) masked_image2 = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') keep_object_ids, keep_object_count = np.unique(masked_image2, return_counts=True) + print("ids: " + str(keep_object_ids)) + print("ids: " + str(keep_object_count)) # Initialize object count object_id_count = 1 # pts in class used for recovering and labeling @@ -248,8 +250,8 @@ def correct_mask(self, bin_img): debug_labels.append(text) if mask_pixel_value > 0: # An object is resolved but check if it's already been annotated - resolved_id = keep_object_ids.index(mask_pixel_value) - if keep_object_count[resolved_id] == 1: + associated_count = keep_object_count[mask_pixel_value] + if associated_count == 1: # New object getting added added_obj_labels.append(mask_pixel_value) analysis_labels.append(names) @@ -259,37 +261,47 @@ def correct_mask(self, bin_img): # Add debug label annotations later debug_coords.append((x, y)) debug_labels.append(text) - if keep_object_count[resolved_id] > 1: - # Object annotated more than once so find original object label - original_index = added_obj_labels.index(mask_pixel_value) - original_label = analysis_labels[original_index] - original_coord = debug_coords[original_index] - # Determine label duplicate or unique for combination - coord_class_label = [k for k, v in self.coords.items() if (x, y) in v] - if coord_class_label[0] in original_label: - # We found a duplicate label - # New object getting added - added_obj_labels.append(object_id_count) - analysis_labels.append(names) - # Fill in the duplicate object in the debug mask - debug_img = np.where(debug_img == original_index, (0), debug_img) - # Replace with pixel annotations in debug - cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) - cv2.circle(debug_img, original_coord, radius=params.line_thickness, color=(original_index), thickness=-1) - # Draw the ghost of objects removed - debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) - # Add debug label annotations later - debug_coords.append((x, y)) - debug_labels.append(text) - # Fill in the duplicate object in the labeled mask, replace with pixel annotations - final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - final_mask[y,x] = object_id_count - final_mask[original_coord[1], original_coord[0]] = original_index + 1 - else: - # If unique then combine labels - analysis_labels[added_obj_labels.index(mask_pixel_value)] = original_label + "_" + coord_class_label[0] - # De-increment object count since just a single object - object_id_count -= 1 + if associated_count > 1: + # Object annotated more than once so find all associated annotations + associated_coords = np.where(masked_image2 == mask_pixel_value) + associated_coords = tuple(zip(*associated_coords)) + coord_labels = [] + for dup_coord in associated_coords: + # Flip x & y for numpy, and find the associated class label with each coordinate + coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] + coord_labels.append(coord_class_label) + print(coord_labels) + _, lbl_count = np.unique(coord_class_label, save_counts=True) + print(lbl_count) + # original_index = added_obj_labels.index(mask_pixel_value) + # original_label = analysis_labels[original_index] + # original_coord = debug_coords[original_index] + # # Determine label duplicate or unique for combination + # coord_class_label = [k for k, v in self.coords.items() if (x, y) in v] + # if coord_class_label[0] in original_label: + # # We found a duplicate label + # # New object getting added + # added_obj_labels.append(object_id_count) + # analysis_labels.append(names) + # # Fill in the duplicate object in the debug mask + # debug_img = np.where(debug_img == original_index, (0), debug_img) + # # Replace with pixel annotations in debug + # cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) + # cv2.circle(debug_img, original_coord, radius=params.line_thickness, color=(original_index), thickness=-1) + # # Draw the ghost of objects removed + # debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + # # Add debug label annotations later + # debug_coords.append((x, y)) + # debug_labels.append(text) + # # Fill in the duplicate object in the labeled mask, replace with pixel annotations + # final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) + # final_mask[y,x] = object_id_count + # final_mask[original_coord[1], original_coord[0]] = original_index + 1 + # else: + # # If unique then combine labels + # analysis_labels[added_obj_labels.index(mask_pixel_value)] = original_label + "_" + coord_class_label[0] + # # De-increment object count since just a single object + # object_id_count -= 1 object_id_count += 1 From 53dfcec94f64959097190f1e0b9a39814fa3f744 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 5 Aug 2024 11:45:25 -0500 Subject: [PATCH 104/162] check for duplication in class labels --- plantcv/annotate/classes.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index df17866..4da7594 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -271,8 +271,8 @@ def correct_mask(self, bin_img): coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] coord_labels.append(coord_class_label) print(coord_labels) - _, lbl_count = np.unique(coord_class_label, save_counts=True) - print(lbl_count) + # If there are duplication in labels (e.g. [['total'], ['total']] then add to list) + dupes = [x for n, x in enumerate(coord_labels) if x in coord_labels[:n]] # original_index = added_obj_labels.index(mask_pixel_value) # original_label = analysis_labels[original_index] # original_coord = debug_coords[original_index] From 9f074eed3c3ee4895d75bb91141297d5f0485a53 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 5 Aug 2024 16:11:11 -0500 Subject: [PATCH 105/162] add logic to check if class labels unique np.unique and if len of this output = 1 then we know two or more annotations with same object resolved back in the bin mask. remove the object from labeled mask and add pixels to the coords --- plantcv/annotate/classes.py | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 4da7594..154ff32 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -223,7 +223,7 @@ def correct_mask(self, bin_img): masked_image2 = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') keep_object_ids, keep_object_count = np.unique(masked_image2, return_counts=True) print("ids: " + str(keep_object_ids)) - print("ids: " + str(keep_object_count)) + print("counts: " + str(keep_object_count)) # Initialize object count object_id_count = 1 # pts in class used for recovering and labeling @@ -271,6 +271,19 @@ def correct_mask(self, bin_img): coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] coord_labels.append(coord_class_label) print(coord_labels) + re, count = np.unique(coord_labels, return_counts=True) + if len(re) == 1: + # Labels are duplicated + # Draw the ghost of objects removed + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + # Fill in the duplicate object in the labeled mask, replace with pixel annotations + final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) + for dup_coord in associated_coords: + final_mask[dup_coord[1], dup_coord[0]] = object_id_count + params.debug = debug + _debug(visual=final_mask, + filename=os.path.join(params.debug_outdir, + f"{params.device}_annotation-corrected.png")) # If there are duplication in labels (e.g. [['total'], ['total']] then add to list) dupes = [x for n, x in enumerate(coord_labels) if x in coord_labels[:n]] # original_index = added_obj_labels.index(mask_pixel_value) From 6ae776ad2f7b074e3e04076b9634d93e13cf065c Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 5 Aug 2024 16:12:01 -0500 Subject: [PATCH 106/162] increment count with each annotation pixel drawn --- plantcv/annotate/classes.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 154ff32..60f6004 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -280,6 +280,8 @@ def correct_mask(self, bin_img): final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) for dup_coord in associated_coords: final_mask[dup_coord[1], dup_coord[0]] = object_id_count + # Increment object count up so each pixel drawn in labeled mask is unique + object_id_count += 1 params.debug = debug _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, From a628152d68cf0747b9ecd7181220a1614fb6ceec Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 5 Aug 2024 16:29:55 -0500 Subject: [PATCH 107/162] concat a flattened list of unique class labels --- plantcv/annotate/classes.py | 21 +++++++++++++++++++++ 1 file changed, 21 insertions(+) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 60f6004..5711408 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -286,6 +286,27 @@ def correct_mask(self, bin_img): _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) + if len(re) > 1: # and count of each label = 1 (count is all "1"s??) + # More than one class label associated with a given object + splitup = [] + # Split on "_" in case something has already been combined + for lbl in re: + list_lbl = lbl[0].split("_") + splitup.append(list_lbl) + + # Flatten list of labels + flat = np.concatenate(splitup) + # Grab each unique label from the list + unique_lbls = np.unique(flat) + # Concat with "_" delimiter + concat_lbl = "_".join(list(unique_lbls)) + # Adding the object + added_obj_labels.append(object_id_count) + analysis_labels.append(concat_lbl) + final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) + # Add debug label annotations later + debug_coords.append((x, y)) + debug_labels.append(text) # If there are duplication in labels (e.g. [['total'], ['total']] then add to list) dupes = [x for n, x in enumerate(coord_labels) if x in coord_labels[:n]] # original_index = added_obj_labels.index(mask_pixel_value) From c3217c3cfdc9189debf600a1a071e13a5b6aae17 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 6 Aug 2024 14:03:43 -0500 Subject: [PATCH 108/162] indent so that dupes "handled" only once --- plantcv/annotate/classes.py | 55 ++++++++++++++++++++++++------------- 1 file changed, 36 insertions(+), 19 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 5711408..c43661f 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -249,7 +249,7 @@ def correct_mask(self, bin_img): debug_coords.append((x, y)) debug_labels.append(text) if mask_pixel_value > 0: - # An object is resolved but check if it's already been annotated + # An object is resolved but check if there are other annotations associated with an object associated_count = keep_object_count[mask_pixel_value] if associated_count == 1: # New object getting added @@ -266,23 +266,34 @@ def correct_mask(self, bin_img): associated_coords = np.where(masked_image2 == mask_pixel_value) associated_coords = tuple(zip(*associated_coords)) coord_labels = [] + # Find all class labels for each annotation for dup_coord in associated_coords: # Flip x & y for numpy, and find the associated class label with each coordinate coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] coord_labels.append(coord_class_label) print(coord_labels) - re, count = np.unique(coord_labels, return_counts=True) + # Is there more than one class label associated with the given object? + re = np.unique(coord_labels) if len(re) == 1: # Labels are duplicated # Draw the ghost of objects removed debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) - # Fill in the duplicate object in the labeled mask, replace with pixel annotations - final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - for dup_coord in associated_coords: - final_mask[dup_coord[1], dup_coord[0]] = object_id_count - # Increment object count up so each pixel drawn in labeled mask is unique - object_id_count += 1 + if mask_pixel_value not in added_obj_labels: + # Fill in the duplicate object in the labeled mask, replace with pixel annotations + final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) + added_obj_labels.append(mask_pixel_value) + for dup_coord in associated_coords: + final_mask[dup_coord[1], dup_coord[0]] = object_id_count + analysis_labels.append(names) + # Add a thicker pixel where unresolved annotation to the debug img + cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) + # Add debug label annotations later + debug_coords.append((dup_coord[1], dup_coord[0])) + debug_labels.append(str(object_id_count)) + # Increment object count up so each pixel drawn in labeled mask is unique + object_id_count += 1 params.debug = debug + print(np.unique(final_mask)) _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) @@ -293,20 +304,26 @@ def correct_mask(self, bin_img): for lbl in re: list_lbl = lbl[0].split("_") splitup.append(list_lbl) - # Flatten list of labels flat = np.concatenate(splitup) # Grab each unique label from the list - unique_lbls = np.unique(flat) - # Concat with "_" delimiter - concat_lbl = "_".join(list(unique_lbls)) - # Adding the object - added_obj_labels.append(object_id_count) - analysis_labels.append(concat_lbl) - final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) - # Add debug label annotations later - debug_coords.append((x, y)) - debug_labels.append(text) + unique_lbls, lbl_counts = np.unique(flat, return_counts=True) + # Is there duplication within each class label for the given object? + if np.all(lbl_counts == 1): + # If no, Concat with "_" delimiter + concat_lbl = "_".join(list(unique_lbls)) + # Adding the object + added_obj_labels.append(object_id_count) + analysis_labels.append(concat_lbl) + final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) + # Add debug label annotations later + debug_coords.append((x, y)) + debug_labels.append(text) + else: + # Draw the ghost of objects removed + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + # Fill in the duplicate object in the labeled mask, replace with pixel annotations + final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) # If there are duplication in labels (e.g. [['total'], ['total']] then add to list) dupes = [x for n, x in enumerate(coord_labels) if x in coord_labels[:n]] # original_index = added_obj_labels.index(mask_pixel_value) From 3f44f6f7a1dbf313baf7729c78cfd7591d0dce24 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 12:58:16 -0500 Subject: [PATCH 109/162] separate the filtering helper function out --- plantcv/annotate/classes.py | 74 ++++++++++++++++++++++++------------- 1 file changed, 49 insertions(+), 25 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index c43661f..a34e455 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -163,8 +163,8 @@ class label, by default "default" for (x, y) in self.coords[self.label]: self.ax.plot(x, y, marker='x', c=self.color) - def correct_mask(self, bin_img): - """Fitler a binary mask and make a labeled mask for analysis. + def _remove_unannotated_objects(self, bin_img): + """Fitler a binary mask based on annotations. Parameters ---------- @@ -173,35 +173,20 @@ def correct_mask(self, bin_img): Returns ---------- - final_mask : numpy.ndarray - corrected and labeled mask with recovered and removed objects - num : int - number of objects represented within the labeled mask + filetered_mask : numpy.ndarray + corrected mask + debug_img_removed : numpy.ndarray + binary mask of objects that were removed """ - from plantcv.plantcv.visualize import colorize_label_img - from plantcv.plantcv import dilate - - debug = params.debug - params.debug = None labelnames = list(self.count) - totalcoor = [] - unrecovered_ids = [] - debug_coords = [] - debug_labels = [] - added_obj_labels = [] - analysis_labels = [] pts_mask = np.zeros(np.shape(bin_img), np.uint8) - final_mask = pts_mask.copy().astype(np.uint32) - debug_img = pts_mask.copy() - debug_img_removed = pts_mask.copy() - debug_img_removed = cv2.cvtColor(debug_img_removed, cv2.COLOR_GRAY2RGB) - debug_img_duplicates = pts_mask.copy() - + debug_img_removed = cv2.cvtColor(pts_mask.copy(), cv2.COLOR_GRAY2RGB) + + # Create points mask from all annotations for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): x = int(x) y = int(y) - totalcoor.append((y, x)) # Draw pt annotations onto a blank mask pts_mask = cv2.circle(pts_mask, (x, y), radius=0, color=(255), thickness=-1) # Create a labeled mask from the input mask @@ -210,14 +195,53 @@ def correct_mask(self, bin_img): # Objects that overlap with one or more annotations get kept masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') keep_object_ids = np.unique(masked_image) - + # Fill in objects that are not overlapping with an annotation for i in range(1, total_obj_num + 1): if i not in keep_object_ids: labeled_mask1[np.where(labeled_mask == i)] = 0 debug_img_removed[np.where(labeled_mask == i)] = (50, 50, 50) + # Create new binary mask after filtering un-annotated objects completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) + + return completed_mask_bin, debug_img_removed + + + def correct_mask(self, bin_img): + """Fitler a binary mask and make a labeled mask for analysis. + + Parameters + ---------- + bin_img : numpy.ndarray + binary image, mask to get corrected + + Returns + ---------- + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects + num : int + number of objects represented within the labeled mask + """ + from plantcv.plantcv.visualize import colorize_label_img + from plantcv.plantcv import dilate + + debug = params.debug + params.debug = None + + unrecovered_ids = [] + debug_coords = [] + debug_labels = [] + added_obj_labels = [] + analysis_labels = [] + + final_mask = np.zeros(np.shape(bin_img), np.uint32) + debug_img = np.zeros(np.shape(bin_img), np.uint8) + + debug_img_duplicates = debug_img.copy() + + completed_mask_bin, debug_img_removed = _remove_unannotated_objects(self, bin_img) + # Create a new labeled annotation mask to determine number of annotation per object labeled_mask_all, _ = create_labels(mask=completed_mask_bin) masked_image2 = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') From c4de635882ec1a4ce07181d3e4e658da240fb248 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 13:25:53 -0500 Subject: [PATCH 110/162] separate out _create_pts_mask function --- plantcv/annotate/classes.py | 38 ++++++++++++++++++++++++++++--------- 1 file changed, 29 insertions(+), 9 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index a34e455..54d46bf 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -163,25 +163,21 @@ class label, by default "default" for (x, y) in self.coords[self.label]: self.ax.plot(x, y, marker='x', c=self.color) - def _remove_unannotated_objects(self, bin_img): + def _create_pts_mask(self, bin_img): """Fitler a binary mask based on annotations. Parameters ---------- bin_img : numpy.ndarray - binary image, mask to get corrected + binary image Returns ---------- - filetered_mask : numpy.ndarray - corrected mask - debug_img_removed : numpy.ndarray - binary mask of objects that were removed + pts_mask : numpy.ndarray + binary mask of annotations """ labelnames = list(self.count) pts_mask = np.zeros(np.shape(bin_img), np.uint8) - debug_img_removed = cv2.cvtColor(pts_mask.copy(), cv2.COLOR_GRAY2RGB) - # Create points mask from all annotations for names in labelnames: for i, (x, y) in enumerate(self.coords[names]): @@ -189,6 +185,28 @@ def _remove_unannotated_objects(self, bin_img): y = int(y) # Draw pt annotations onto a blank mask pts_mask = cv2.circle(pts_mask, (x, y), radius=0, color=(255), thickness=-1) + + return pts_mask + + def _remove_unannotated_objects(pts_mask, bin_img): + """Fitler a binary mask based on annotations. + + Parameters + ---------- + pts_mask : numpy.ndarray + binary image, mask with all annotations plotted as pixels + bin_img : numpy.ndarray + binary image, mask to get corrected + + Returns + ---------- + filetered_mask : numpy.ndarray + corrected mask + debug_img_removed : numpy.ndarray + binary mask of objects that were removed + """ + debug_img_removed = cv2.cvtColor(pts_mask.copy(), cv2.COLOR_GRAY2RGB) + # Create a labeled mask from the input mask labeled_mask, total_obj_num = create_labels(mask=bin_img) labeled_mask1 = np.copy(labeled_mask) @@ -235,12 +253,14 @@ def correct_mask(self, bin_img): added_obj_labels = [] analysis_labels = [] + pts_mask = _create_pts_mask(bin_img) + final_mask = np.zeros(np.shape(bin_img), np.uint32) debug_img = np.zeros(np.shape(bin_img), np.uint8) debug_img_duplicates = debug_img.copy() - completed_mask_bin, debug_img_removed = _remove_unannotated_objects(self, bin_img) + completed_mask_bin, debug_img_removed = _remove_unannotated_objects(pts_mask, bin_img) # Create a new labeled annotation mask to determine number of annotation per object labeled_mask_all, _ = create_labels(mask=completed_mask_bin) From 17bb3881ba7f4359ce16c177201527082ffb3a94 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 13:32:55 -0500 Subject: [PATCH 111/162] filtering helper as function rather than method --- plantcv/annotate/classes.py | 75 +++++++++++++++++++------------------ 1 file changed, 38 insertions(+), 37 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 54d46bf..a1f2fb8 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -188,43 +188,6 @@ def _create_pts_mask(self, bin_img): return pts_mask - def _remove_unannotated_objects(pts_mask, bin_img): - """Fitler a binary mask based on annotations. - - Parameters - ---------- - pts_mask : numpy.ndarray - binary image, mask with all annotations plotted as pixels - bin_img : numpy.ndarray - binary image, mask to get corrected - - Returns - ---------- - filetered_mask : numpy.ndarray - corrected mask - debug_img_removed : numpy.ndarray - binary mask of objects that were removed - """ - debug_img_removed = cv2.cvtColor(pts_mask.copy(), cv2.COLOR_GRAY2RGB) - - # Create a labeled mask from the input mask - labeled_mask, total_obj_num = create_labels(mask=bin_img) - labeled_mask1 = np.copy(labeled_mask) - # Objects that overlap with one or more annotations get kept - masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') - keep_object_ids = np.unique(masked_image) - - # Fill in objects that are not overlapping with an annotation - for i in range(1, total_obj_num + 1): - if i not in keep_object_ids: - labeled_mask1[np.where(labeled_mask == i)] = 0 - debug_img_removed[np.where(labeled_mask == i)] = (50, 50, 50) - - # Create new binary mask after filtering un-annotated objects - completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) - - return completed_mask_bin, debug_img_removed - def correct_mask(self, bin_img): """Fitler a binary mask and make a labeled mask for analysis. @@ -424,3 +387,41 @@ def correct_mask(self, bin_img): num = len(np.unique(final_mask)) - 1 return final_mask, analysis_labels, num + + +def _remove_unannotated_objects(pts_mask, bin_img): + """Fitler a binary mask based on annotations. + + Parameters + ---------- + pts_mask : numpy.ndarray + binary image, mask with all annotations plotted as pixels + bin_img : numpy.ndarray + binary image, mask to get corrected + + Returns + ---------- + filetered_mask : numpy.ndarray + corrected mask + debug_img_removed : numpy.ndarray + binary mask of objects that were removed + """ + debug_img_removed = cv2.cvtColor(pts_mask.copy(), cv2.COLOR_GRAY2RGB) + + # Create a labeled mask from the input mask + labeled_mask, total_obj_num = create_labels(mask=bin_img) + labeled_mask1 = np.copy(labeled_mask) + # Objects that overlap with one or more annotations get kept + masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') + keep_object_ids = np.unique(masked_image) + + # Fill in objects that are not overlapping with an annotation + for i in range(1, total_obj_num + 1): + if i not in keep_object_ids: + labeled_mask1[np.where(labeled_mask == i)] = 0 + debug_img_removed[np.where(labeled_mask == i)] = (50, 50, 50) + + # Create new binary mask after filtering un-annotated objects + completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) + + return completed_mask_bin, debug_img_removed \ No newline at end of file From c1cf979682fcd4d9a33362863b18ee3e228ef3d8 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 13:33:15 -0500 Subject: [PATCH 112/162] reference _create_pts_mask as method --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index a1f2fb8..3b7af9b 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -216,7 +216,7 @@ def correct_mask(self, bin_img): added_obj_labels = [] analysis_labels = [] - pts_mask = _create_pts_mask(bin_img) + pts_mask = self._create_pts_mask(bin_img) final_mask = np.zeros(np.shape(bin_img), np.uint32) debug_img = np.zeros(np.shape(bin_img), np.uint8) From fad6b6efc1bcd16d72dd6fa1719c0269ee66c031 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 13:44:19 -0500 Subject: [PATCH 113/162] make labelnames an input for create_pts_mask helper --- plantcv/annotate/classes.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 3b7af9b..144f57d 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -163,7 +163,8 @@ class label, by default "default" for (x, y) in self.coords[self.label]: self.ax.plot(x, y, marker='x', c=self.color) - def _create_pts_mask(self, bin_img): + + def _create_pts_mask(self, bin_img, labelnames): """Fitler a binary mask based on annotations. Parameters @@ -176,7 +177,6 @@ def _create_pts_mask(self, bin_img): pts_mask : numpy.ndarray binary mask of annotations """ - labelnames = list(self.count) pts_mask = np.zeros(np.shape(bin_img), np.uint8) # Create points mask from all annotations for names in labelnames: @@ -216,7 +216,9 @@ def correct_mask(self, bin_img): added_obj_labels = [] analysis_labels = [] - pts_mask = self._create_pts_mask(bin_img) + labelnames = list(self.count) + + pts_mask = self._create_pts_mask(bin_img, labelnames) final_mask = np.zeros(np.shape(bin_img), np.uint32) debug_img = np.zeros(np.shape(bin_img), np.uint8) From 23e1d1374b3b090a213ef37762498e5336d99c79 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 14:05:49 -0500 Subject: [PATCH 114/162] capture the adtl return to tests --- tests/test_annotate_points.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 07d8790..0220f9c 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -184,7 +184,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") - corrected_mask, _ = counter.correct_mask(bin_img=allmask) + corrected_mask, _, _ = counter.correct_mask(bin_img=allmask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(discs) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) From 04fc6f774ac93ba8116bdc54b46c2e441bc2c20f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 14:16:53 -0500 Subject: [PATCH 115/162] simplify for loop --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 144f57d..d6f1fc1 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -180,7 +180,7 @@ def _create_pts_mask(self, bin_img, labelnames): pts_mask = np.zeros(np.shape(bin_img), np.uint8) # Create points mask from all annotations for names in labelnames: - for i, (x, y) in enumerate(self.coords[names]): + for (x, y) in self.coords[names]: x = int(x) y = int(y) # Draw pt annotations onto a blank mask From 5f633241d2cfd36122c401a4dc91ebe98d5b36ae Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 15:10:32 -0500 Subject: [PATCH 116/162] simplfy for loop and add _draw_unresolved_object --- plantcv/annotate/classes.py | 71 +++++++++++++++++++------------------ 1 file changed, 36 insertions(+), 35 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index d6f1fc1..79e435b 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -237,12 +237,11 @@ def correct_mask(self, bin_img): object_id_count = 1 # pts in class used for recovering and labeling for names in labelnames: - for i, (x, y) in enumerate(self.coords[names]): + for (x, y) in self.coords[names]: x = int(x) y = int(y) mask_pixel_value = labeled_mask_all[y, x] text = str(object_id_count) - # Check if current annotation can be resolved to an object in the mask if mask_pixel_value == 0: if params.verbose == True: @@ -251,9 +250,7 @@ def correct_mask(self, bin_img): added_obj_labels.append(object_id_count) analysis_labels.append(names) # Add a pixel where unresolved annotation to the mask - final_mask[y,x] = object_id_count - # Add a thicker pixel where unresolved annotation to the debug img - cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) + debug_img, final_mask, object_id_count = _draw_unresolved_object(debug_img, final_mask, obj_number=object_id_count, coord=(x, y)) # Add debug label annotations later debug_coords.append((x, y)) debug_labels.append(text) @@ -335,35 +332,6 @@ def correct_mask(self, bin_img): final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) # If there are duplication in labels (e.g. [['total'], ['total']] then add to list) dupes = [x for n, x in enumerate(coord_labels) if x in coord_labels[:n]] - # original_index = added_obj_labels.index(mask_pixel_value) - # original_label = analysis_labels[original_index] - # original_coord = debug_coords[original_index] - # # Determine label duplicate or unique for combination - # coord_class_label = [k for k, v in self.coords.items() if (x, y) in v] - # if coord_class_label[0] in original_label: - # # We found a duplicate label - # # New object getting added - # added_obj_labels.append(object_id_count) - # analysis_labels.append(names) - # # Fill in the duplicate object in the debug mask - # debug_img = np.where(debug_img == original_index, (0), debug_img) - # # Replace with pixel annotations in debug - # cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(object_id_count), thickness=-1) - # cv2.circle(debug_img, original_coord, radius=params.line_thickness, color=(original_index), thickness=-1) - # # Draw the ghost of objects removed - # debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) - # # Add debug label annotations later - # debug_coords.append((x, y)) - # debug_labels.append(text) - # # Fill in the duplicate object in the labeled mask, replace with pixel annotations - # final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - # final_mask[y,x] = object_id_count - # final_mask[original_coord[1], original_coord[0]] = original_index + 1 - # else: - # # If unique then combine labels - # analysis_labels[added_obj_labels.index(mask_pixel_value)] = original_label + "_" + coord_class_label[0] - # # De-increment object count since just a single object - # object_id_count -= 1 object_id_count += 1 @@ -426,4 +394,37 @@ def _remove_unannotated_objects(pts_mask, bin_img): # Create new binary mask after filtering un-annotated objects completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) - return completed_mask_bin, debug_img_removed \ No newline at end of file + return completed_mask_bin, debug_img_removed + + +def _draw_unresolved_object(debug_img, final_mask, obj_number, coord): + """Fitler a binary mask based on annotations. + + Parameters + ---------- + debug_img : numpy.ndarray + debug image of objects, unresolved annotations, etc + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects + obj_number : int + ID number for the current object getting added + coord : tuple + coordinate of the unresolved object annotation + + Returns + ---------- + debug_img : numpy.ndarray + debug image of objects, unresolved annotations, etc + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects + obj_number : int + ID number for the current object getting added + """ + (x, y) = coord + # Add a pixel where unresolved annotation to the mask + final_mask[y,x] = obj_number + # Add a thicker pixel where unresolved annotation to the debug img + cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(obj_number), thickness=-1) + # Increment ID number up by one + obj_number += 1 + return debug_img, final_mask, obj_number From fadf20e0f6761092f887c58eb0f7f9fbe6b5152b Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 15:30:29 -0500 Subject: [PATCH 117/162] add _draw_resolved --- plantcv/annotate/classes.py | 40 ++++++++++++++++++++++++++++++++++--- 1 file changed, 37 insertions(+), 3 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 79e435b..365ec2f 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -249,11 +249,11 @@ def correct_mask(self, bin_img): unrecovered_ids.append(object_id_count) added_obj_labels.append(object_id_count) analysis_labels.append(names) - # Add a pixel where unresolved annotation to the mask - debug_img, final_mask, object_id_count = _draw_unresolved_object(debug_img, final_mask, obj_number=object_id_count, coord=(x, y)) # Add debug label annotations later debug_coords.append((x, y)) debug_labels.append(text) + # Add the unresolved object to the labeled mask and the debug img + debug_img, final_mask, object_id_count = _draw_unresolved_object(debug_img, final_mask, obj_number=object_id_count, coord=(x, y)) if mask_pixel_value > 0: # An object is resolved but check if there are other annotations associated with an object associated_count = keep_object_count[mask_pixel_value] @@ -398,7 +398,7 @@ def _remove_unannotated_objects(pts_mask, bin_img): def _draw_unresolved_object(debug_img, final_mask, obj_number, coord): - """Fitler a binary mask based on annotations. + """Draw unresolved objects as a labeled pixel Parameters ---------- @@ -428,3 +428,37 @@ def _draw_unresolved_object(debug_img, final_mask, obj_number, coord): # Increment ID number up by one obj_number += 1 return debug_img, final_mask, obj_number + + +def _draw_resolved(debug_img, final_mask, pre_lbls_mask, mask_pixel_value, obj_number): + """Draw resolved/measurable objects + + Parameters + ---------- + debug_img : numpy.ndarray + debug image of objects, unresolved annotations, etc + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects + pre_lbls_mask : numpy.ndarray + labeled mask of all resolvable objects + mask_pixel_value : int + ID number for the current resolved object in pre_lbls_mask + obj_number : int + ID number for the current object getting added + + Returns + ---------- + debug_img : numpy.ndarray + debug image of objects, unresolved annotations, etc + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects + obj_number : int + ID number for the current object getting added + """ + # Add a pixel where unresolved annotation to the mask + # Draw on labeled mask + final_mask = np.where(pre_lbls_mask == mask_pixel_value, obj_number, final_mask) + debug_img = np.where(pre_lbls_mask == mask_pixel_value, obj_number, debug_img) + # Increment ID number up by one + obj_number += 1 + return debug_img, final_mask, obj_number From e132146c2bd975902b51d10f3c63d1d781af8054 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 15:45:12 -0500 Subject: [PATCH 118/162] utilize _draw_resolved and remove some debug duplicates --- plantcv/annotate/classes.py | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 365ec2f..c479db4 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -261,12 +261,12 @@ def correct_mask(self, bin_img): # New object getting added added_obj_labels.append(mask_pixel_value) analysis_labels.append(names) - # Draw on labeled mask with correct pixel value - final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) - debug_img = np.where(labeled_mask_all == mask_pixel_value, object_id_count, debug_img) # Add debug label annotations later debug_coords.append((x, y)) debug_labels.append(text) + # Draw on labeled mask and debug img + debug_img, final_mask, object_id_count = _draw_resolved(debug_img, final_mask, labeled_mask_all, + mask_pixel_value, object_id_count) if associated_count > 1: # Object annotated more than once so find all associated annotations associated_coords = np.where(masked_image2 == mask_pixel_value) @@ -298,11 +298,7 @@ def correct_mask(self, bin_img): debug_labels.append(str(object_id_count)) # Increment object count up so each pixel drawn in labeled mask is unique object_id_count += 1 - params.debug = debug print(np.unique(final_mask)) - _debug(visual=final_mask, - filename=os.path.join(params.debug_outdir, - f"{params.device}_annotation-corrected.png")) if len(re) > 1: # and count of each label = 1 (count is all "1"s??) # More than one class label associated with a given object splitup = [] @@ -321,10 +317,12 @@ def correct_mask(self, bin_img): # Adding the object added_obj_labels.append(object_id_count) analysis_labels.append(concat_lbl) - final_mask = np.where(labeled_mask_all == mask_pixel_value, object_id_count, final_mask) # Add debug label annotations later debug_coords.append((x, y)) debug_labels.append(text) + # Draw on labeled mask and debug img + debug_img, final_mask, object_id_count = _draw_resolved( + debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) else: # Draw the ghost of objects removed debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) From fbf9fc216b72012e76a8f7004eb9e6c2ff382e05 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 15:57:12 -0500 Subject: [PATCH 119/162] Stop incrementing object ID at the loop and dupe check MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit add a check for whether a duplicate annotated object has been “analyzed” --- plantcv/annotate/classes.py | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index c479db4..87d9168 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -324,15 +324,14 @@ def correct_mask(self, bin_img): debug_img, final_mask, object_id_count = _draw_resolved( debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) else: - # Draw the ghost of objects removed - debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) - # Fill in the duplicate object in the labeled mask, replace with pixel annotations - final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) + if mask_pixel_value not in added_obj_labels: + # Draw the ghost of objects removed + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + # Fill in the duplicate object in the labeled mask, replace with pixel annotations + final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) # If there are duplication in labels (e.g. [['total'], ['total']] then add to list) dupes = [x for n, x in enumerate(coord_labels) if x in coord_labels[:n]] - object_id_count += 1 - # Combine and colorize the debug image # Dilate duplicate objs and subtract the object itself to leave just a halo around debug_img_duplicates1 = dilate(debug_img_duplicates, ksize=params.line_thickness, i=1) From daf2e8e1ce407d8b3f231a286d5bbf02ca8a006d Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 13 Aug 2024 16:45:17 -0500 Subject: [PATCH 120/162] unique class double annotate case, also check for previous handling switch dup_coord order for final mask plotting of unresolved total_total cases --- plantcv/annotate/classes.py | 123 ++++++++++++++++++------------------ 1 file changed, 62 insertions(+), 61 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 87d9168..c8b61b7 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -268,69 +268,70 @@ def correct_mask(self, bin_img): debug_img, final_mask, object_id_count = _draw_resolved(debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) if associated_count > 1: - # Object annotated more than once so find all associated annotations - associated_coords = np.where(masked_image2 == mask_pixel_value) - associated_coords = tuple(zip(*associated_coords)) - coord_labels = [] - # Find all class labels for each annotation - for dup_coord in associated_coords: - # Flip x & y for numpy, and find the associated class label with each coordinate - coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] - coord_labels.append(coord_class_label) - print(coord_labels) - # Is there more than one class label associated with the given object? - re = np.unique(coord_labels) - if len(re) == 1: - # Labels are duplicated - # Draw the ghost of objects removed - debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) - if mask_pixel_value not in added_obj_labels: - # Fill in the duplicate object in the labeled mask, replace with pixel annotations - final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - added_obj_labels.append(mask_pixel_value) - for dup_coord in associated_coords: - final_mask[dup_coord[1], dup_coord[0]] = object_id_count - analysis_labels.append(names) - # Add a thicker pixel where unresolved annotation to the debug img - cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) - # Add debug label annotations later - debug_coords.append((dup_coord[1], dup_coord[0])) - debug_labels.append(str(object_id_count)) - # Increment object count up so each pixel drawn in labeled mask is unique - object_id_count += 1 - print(np.unique(final_mask)) - if len(re) > 1: # and count of each label = 1 (count is all "1"s??) - # More than one class label associated with a given object - splitup = [] - # Split on "_" in case something has already been combined - for lbl in re: - list_lbl = lbl[0].split("_") - splitup.append(list_lbl) - # Flatten list of labels - flat = np.concatenate(splitup) - # Grab each unique label from the list - unique_lbls, lbl_counts = np.unique(flat, return_counts=True) - # Is there duplication within each class label for the given object? - if np.all(lbl_counts == 1): - # If no, Concat with "_" delimiter - concat_lbl = "_".join(list(unique_lbls)) - # Adding the object - added_obj_labels.append(object_id_count) - analysis_labels.append(concat_lbl) - # Add debug label annotations later - debug_coords.append((x, y)) - debug_labels.append(text) - # Draw on labeled mask and debug img - debug_img, final_mask, object_id_count = _draw_resolved( - debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) - else: + # Has this object been handled already? + if mask_pixel_value not in added_obj_labels: + # Object annotated more than once so find all associated annotations + associated_coords = np.where(masked_image2 == mask_pixel_value) + associated_coords = tuple(zip(*associated_coords)) + coord_labels = [] + # Find all class labels for each annotation + for dup_coord in associated_coords: + # Flip x & y for numpy, and find the associated class label with each coordinate + coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] + coord_labels.append(coord_class_label) + print(coord_labels) + # Is there more than one class label associated with the given object? + re = np.unique(coord_labels) + if len(re) == 1: + # Labels are duplicated e.g. "total", "total" + # Draw the ghost of objects removed + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) if mask_pixel_value not in added_obj_labels: - # Draw the ghost of objects removed - debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) # Fill in the duplicate object in the labeled mask, replace with pixel annotations final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - # If there are duplication in labels (e.g. [['total'], ['total']] then add to list) - dupes = [x for n, x in enumerate(coord_labels) if x in coord_labels[:n]] + added_obj_labels.append(mask_pixel_value) + for dup_coord in associated_coords: + final_mask[dup_coord] = object_id_count + analysis_labels.append(names) + # Add a thicker pixel where unresolved annotation to the debug img + cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) + # Add debug label annotations later + debug_coords.append((dup_coord[1], dup_coord[0])) + debug_labels.append(str(object_id_count)) + # Increment object count up so each pixel drawn in labeled mask is unique + object_id_count += 1 + print(np.unique(final_mask)) + if len(re) > 1: # and count of each label = 1 (count is all "1"s??) + # More than one class label associated with a given object + splitup = [] + # Split on "_" in case something has already been combined + for lbl in re: + list_lbl = lbl[0].split("_") + splitup.append(list_lbl) + # Flatten list of labels + flat = np.concatenate(splitup) + # Grab each unique label from the list + unique_lbls, lbl_counts = np.unique(flat, return_counts=True) + # Is there duplication within each class label for the given object? + if np.all(lbl_counts == 1): + if mask_pixel_value not in added_obj_labels: + # If no, Concat with "_" delimiter + concat_lbl = "_".join(list(unique_lbls)) + # Adding the object + added_obj_labels.append(object_id_count) + analysis_labels.append(concat_lbl) + # Draw on labeled mask and debug img + debug_img, final_mask, object_id_count = _draw_resolved( + debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) + else: + if mask_pixel_value not in added_obj_labels: + added_obj_labels.append(mask_pixel_value) + # Draw the ghost of objects removed + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + # Fill in the duplicate object in the labeled mask, replace with pixel annotations + final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) + # If there are duplication in labels (e.g. [['total'], ['total']] then add to list) + dupes = [x for n, x in enumerate(coord_labels) if x in coord_labels[:n]] # Combine and colorize the debug image # Dilate duplicate objs and subtract the object itself to leave just a halo around @@ -419,7 +420,7 @@ def _draw_unresolved_object(debug_img, final_mask, obj_number, coord): """ (x, y) = coord # Add a pixel where unresolved annotation to the mask - final_mask[y,x] = obj_number + final_mask[y, x] = obj_number # Add a thicker pixel where unresolved annotation to the debug img cv2.circle(debug_img, (x, y), radius=params.line_thickness, color=(obj_number), thickness=-1) # Increment ID number up by one From a58e67d775856f34a3669792dc150d6d1bf3f113 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 15 Aug 2024 09:25:26 -0500 Subject: [PATCH 121/162] new helper _draw_ghost_of_duplicates_removed also temp comments and debug statements --- plantcv/annotate/classes.py | 40 ++++++++++++++++++++++++++++++------- 1 file changed, 33 insertions(+), 7 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index c8b61b7..f2b282b 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -205,7 +205,6 @@ def correct_mask(self, bin_img): number of objects represented within the labeled mask """ from plantcv.plantcv.visualize import colorize_label_img - from plantcv.plantcv import dilate debug = params.debug params.debug = None @@ -291,6 +290,7 @@ def correct_mask(self, bin_img): final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) added_obj_labels.append(mask_pixel_value) for dup_coord in associated_coords: + # Draw each pixel in the final mask final_mask[dup_coord] = object_id_count analysis_labels.append(names) # Add a thicker pixel where unresolved annotation to the debug img @@ -320,10 +320,14 @@ def correct_mask(self, bin_img): # Adding the object added_obj_labels.append(object_id_count) analysis_labels.append(concat_lbl) + # Add debug label annotations later + #debug_coords.append((associated_coords[0])) # Draw on labeled mask and debug img debug_img, final_mask, object_id_count = _draw_resolved( debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) + else: + # "total", "total", "germinated" is too complex to measure so if mask_pixel_value not in added_obj_labels: added_obj_labels.append(mask_pixel_value) # Draw the ghost of objects removed @@ -333,14 +337,13 @@ def correct_mask(self, bin_img): # If there are duplication in labels (e.g. [['total'], ['total']] then add to list) dupes = [x for n, x in enumerate(coord_labels) if x in coord_labels[:n]] - # Combine and colorize the debug image - # Dilate duplicate objs and subtract the object itself to leave just a halo around - debug_img_duplicates1 = dilate(debug_img_duplicates, ksize=params.line_thickness, i=1) - debug_img_duplicates = debug_img_duplicates1 - debug_img_duplicates - debug_img_duplicates = cv2.cvtColor(debug_img_duplicates, cv2.COLOR_GRAY2RGB) + # Combine and colorize components of the debug image + debug_img_duplicates_rgb = _draw_ghost_of_duplicates_removed(debug_img_duplicates) debug_img = colorize_label_img(debug_img) - debug_img = debug_img + debug_img_removed + debug_img_duplicates + debug_img = debug_img + debug_img_removed + debug_img_duplicates_rgb + # Write ID labels + print("debug labels:" + str(debug_labels)) for id, id_label in enumerate(debug_labels): cv2.putText(img=debug_img, text=id_label, org=debug_coords[id], fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=params.text_size, color=(150, 150, 150), thickness=params.text_thickness) @@ -460,3 +463,26 @@ def _draw_resolved(debug_img, final_mask, pre_lbls_mask, mask_pixel_value, obj_n # Increment ID number up by one obj_number += 1 return debug_img, final_mask, obj_number + +def _draw_ghost_of_duplicates_removed(dupes_mask): + """Fitler a binary mask based on annotations. + + Parameters + ---------- + dupes_mask : numpy.ndarray + binary image, mask with all removed (because duplicate annotations) objects + removed_mask : numpy.ndarray + binary image, mask of unannotated and removed objects + + Returns + ---------- + removed_mask : numpy.ndarray + combined mask with all removed objects for debug visualization + """ + from plantcv.plantcv import dilate + + # Dilate duplicate objs and subtract the object itself to leave just a halo around + debug_img_duplicates = dilate(dupes_mask, ksize=params.line_thickness, i=1) + debug_img_duplicates = debug_img_duplicates - dupes_mask + debug_img_duplicates = cv2.cvtColor(debug_img_duplicates, cv2.COLOR_GRAY2RGB) + return debug_img_duplicates \ No newline at end of file From 2533ac1c374bb4c1b42cfa232e7c9aed7923a5dc Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 15 Aug 2024 09:38:22 -0500 Subject: [PATCH 122/162] always append mask_pixel_value meant to keep track of objects rather than annotations --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index f2b282b..03480e2 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -318,7 +318,7 @@ def correct_mask(self, bin_img): # If no, Concat with "_" delimiter concat_lbl = "_".join(list(unique_lbls)) # Adding the object - added_obj_labels.append(object_id_count) + added_obj_labels.append(mask_pixel_value) analysis_labels.append(concat_lbl) # Add debug label annotations later #debug_coords.append((associated_coords[0])) From e2ec3ae14b5135a299fbe940b2a0e21bdefd098e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 15 Aug 2024 11:50:09 -0500 Subject: [PATCH 123/162] remove print statements and grab entire class labels [0] was grabbing just the first character from each string of class label, add print statement for combining labels, and uncomment the parts where debug labels are getting added --- plantcv/annotate/classes.py | 27 +++++++++++++-------------- 1 file changed, 13 insertions(+), 14 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 03480e2..95f60eb 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -230,8 +230,6 @@ def correct_mask(self, bin_img): labeled_mask_all, _ = create_labels(mask=completed_mask_bin) masked_image2 = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') keep_object_ids, keep_object_count = np.unique(masked_image2, return_counts=True) - print("ids: " + str(keep_object_ids)) - print("counts: " + str(keep_object_count)) # Initialize object count object_id_count = 1 # pts in class used for recovering and labeling @@ -278,7 +276,6 @@ def correct_mask(self, bin_img): # Flip x & y for numpy, and find the associated class label with each coordinate coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] coord_labels.append(coord_class_label) - print(coord_labels) # Is there more than one class label associated with the given object? re = np.unique(coord_labels) if len(re) == 1: @@ -300,16 +297,15 @@ def correct_mask(self, bin_img): debug_labels.append(str(object_id_count)) # Increment object count up so each pixel drawn in labeled mask is unique object_id_count += 1 - print(np.unique(final_mask)) - if len(re) > 1: # and count of each label = 1 (count is all "1"s??) + if len(re) > 1: # More than one class label associated with a given object - splitup = [] + splitup = np.empty((len(re), 1), dtype='U25') # Split on "_" in case something has already been combined - for lbl in re: - list_lbl = lbl[0].split("_") - splitup.append(list_lbl) + for k, lbl in enumerate(re): + list_lbl = lbl.split("_") + splitup[k] = list_lbl # Flatten list of labels - flat = np.concatenate(splitup) + flat = np.concatenate(splitup, dtype=' Date: Thu, 15 Aug 2024 11:58:46 -0500 Subject: [PATCH 124/162] check if object already "handled" in just the upstream place --- plantcv/annotate/classes.py | 72 ++++++++++++++++++------------------- 1 file changed, 34 insertions(+), 38 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 95f60eb..9968c6d 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -282,21 +282,20 @@ def correct_mask(self, bin_img): # Labels are duplicated e.g. "total", "total" # Draw the ghost of objects removed debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) - if mask_pixel_value not in added_obj_labels: - # Fill in the duplicate object in the labeled mask, replace with pixel annotations - final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - added_obj_labels.append(mask_pixel_value) - for dup_coord in associated_coords: - # Draw each pixel in the final mask - final_mask[dup_coord] = object_id_count - analysis_labels.append(names) - # Add a thicker pixel where unresolved annotation to the debug img - cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) - # Add debug label annotations later - debug_coords.append((dup_coord[1], dup_coord[0])) - debug_labels.append(str(object_id_count)) - # Increment object count up so each pixel drawn in labeled mask is unique - object_id_count += 1 + # Fill in the duplicate object in the labeled mask, replace with pixel annotations + final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) + added_obj_labels.append(mask_pixel_value) + for dup_coord in associated_coords: + # Draw each pixel in the final mask + final_mask[dup_coord] = object_id_count + analysis_labels.append(names) + # Add a thicker pixel where unresolved annotation to the debug img + cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) + # Add debug label annotations later + debug_coords.append((dup_coord[1], dup_coord[0])) + debug_labels.append(str(object_id_count)) + # Increment object count up so each pixel drawn in labeled mask is unique + object_id_count += 1 if len(re) > 1: # More than one class label associated with a given object splitup = np.empty((len(re), 1), dtype='U25') @@ -310,32 +309,29 @@ def correct_mask(self, bin_img): unique_lbls, lbl_counts = np.unique(flat, return_counts=True) # Is there duplication within each class label for the given object? if np.all(lbl_counts == 1): - if mask_pixel_value not in added_obj_labels: - # If no, Concat with "_" delimiter - concat_lbl = "_".join(list(unique_lbls)) - # Adding the object - added_obj_labels.append(mask_pixel_value) - analysis_labels.append(concat_lbl) - # Add debug label annotations later - first_coord = (associated_coords[0][1], associated_coords[0][0]) - if params.verbose == True: - print("labels getting concatenated to '{0}' at {1}".format(str(concat_lbl), str(first_coord))) - debug_coords.append(first_coord) - debug_labels.append(str(object_id_count)) - - # Draw on labeled mask and debug img - debug_img, final_mask, object_id_count = _draw_resolved( - debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) + # If no, Concat with "_" delimiter + concat_lbl = "_".join(list(unique_lbls)) + # Adding the object + added_obj_labels.append(mask_pixel_value) + analysis_labels.append(concat_lbl) + # Add debug label annotations later + first_coord = (associated_coords[0][1], associated_coords[0][0]) + if params.verbose == True: + print("labels getting concatenated to '{0}' at {1}".format(str(concat_lbl), str(first_coord))) + debug_coords.append(first_coord) + debug_labels.append(str(object_id_count)) + # Draw on labeled mask and debug img + debug_img, final_mask, object_id_count = _draw_resolved( + debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) else: # "total", "total", "germinated" is too complex to measure so - if mask_pixel_value not in added_obj_labels: - added_obj_labels.append(mask_pixel_value) - # Draw the ghost of objects removed - debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) - # Fill in the duplicate object in the labeled mask, replace with pixel annotations - final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - ### ADD PIXEL ANNOTATIONS TO FINAL MASK AND TO DEBUG + added_obj_labels.append(mask_pixel_value) + # Draw the ghost of objects removed + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + # Fill in the duplicate object in the labeled mask, replace with pixel annotations + final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) + ### ADD PIXEL ANNOTATIONS TO FINAL MASK AND TO DEBUG # Combine and colorize components of the debug image debug_img_duplicates_rgb = _draw_ghost_of_duplicates_removed(debug_img_duplicates) From da974e083bc841a4f86366d0ab05b159b1eb5a1b Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 15 Aug 2024 12:02:19 -0500 Subject: [PATCH 125/162] change line_thickness since dilate will err if ksize=1 --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 9968c6d..c58142a 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -341,7 +341,7 @@ def correct_mask(self, bin_img): # Write ID labels for id, id_label in enumerate(debug_labels): cv2.putText(img=debug_img, text=id_label, org=debug_coords[id], fontFace=cv2.FONT_HERSHEY_SIMPLEX, - fontScale=params.text_size, color=(150, 150, 150), thickness=params.text_thickness) + fontScale=params.text_size, color=(150, 150, 150), thickness=(params.text_thickness+2)) params.debug = debug # _debug(visual=final_mask, # filename=os.path.join(params.debug_outdir, From 92f7ebc541f7eb3ea894c15571f6a2d317bdcd01 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 15 Aug 2024 13:05:23 -0500 Subject: [PATCH 126/162] added the inc in thickness at the wrong spot --- plantcv/annotate/classes.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index c58142a..7713692 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -325,6 +325,7 @@ def correct_mask(self, bin_img): debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) else: + print("The follow labels were associated and could not be resolved: " + str(flat)) # "total", "total", "germinated" is too complex to measure so added_obj_labels.append(mask_pixel_value) # Draw the ghost of objects removed @@ -341,7 +342,7 @@ def correct_mask(self, bin_img): # Write ID labels for id, id_label in enumerate(debug_labels): cv2.putText(img=debug_img, text=id_label, org=debug_coords[id], fontFace=cv2.FONT_HERSHEY_SIMPLEX, - fontScale=params.text_size, color=(150, 150, 150), thickness=(params.text_thickness+2)) + fontScale=params.text_size, color=(150, 150, 150), thickness=(params.text_thickness)) params.debug = debug # _debug(visual=final_mask, # filename=os.path.join(params.debug_outdir, @@ -477,7 +478,7 @@ def _draw_ghost_of_duplicates_removed(dupes_mask): from plantcv.plantcv import dilate # Dilate duplicate objs and subtract the object itself to leave just a halo around - debug_img_duplicates = dilate(dupes_mask, ksize=params.line_thickness, i=1) + debug_img_duplicates = dilate(dupes_mask, ksize=params.line_thickness+2, i=1) debug_img_duplicates = debug_img_duplicates - dupes_mask debug_img_duplicates = cv2.cvtColor(debug_img_duplicates, cv2.COLOR_GRAY2RGB) return debug_img_duplicates \ No newline at end of file From 797482df0a931175589480ad8865f518eb021564 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 15 Aug 2024 13:53:56 -0500 Subject: [PATCH 127/162] update logic for the most complex cases and add print statemtnt --- plantcv/annotate/classes.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 7713692..d72a335 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -277,7 +277,7 @@ def correct_mask(self, bin_img): coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] coord_labels.append(coord_class_label) # Is there more than one class label associated with the given object? - re = np.unique(coord_labels) + re, rep = np.unique(coord_labels, return_counts=True) if len(re) == 1: # Labels are duplicated e.g. "total", "total" # Draw the ghost of objects removed @@ -298,11 +298,13 @@ def correct_mask(self, bin_img): object_id_count += 1 if len(re) > 1: # More than one class label associated with a given object - splitup = np.empty((len(re), 1), dtype='U25') + splitup = [] # Split on "_" in case something has already been combined - for k, lbl in enumerate(re): - list_lbl = lbl.split("_") - splitup[k] = list_lbl + for lbls in coord_labels: + list_lbl = [] + for lbl in lbls: + list_lbl.append(lbl.split("_")) + splitup.append(np.concatenate(list_lbl)) # Flatten list of labels flat = np.concatenate(splitup, dtype=' Date: Fri, 16 Aug 2024 11:16:17 -0500 Subject: [PATCH 128/162] add _add_debug_id and utilize plus code cleanup from some unused variables --- plantcv/annotate/classes.py | 69 +++++++++++++++++++++++++------------ 1 file changed, 47 insertions(+), 22 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index d72a335..e06a237 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -208,20 +208,16 @@ def correct_mask(self, bin_img): debug = params.debug params.debug = None - + # Initialize lists and arrays unrecovered_ids = [] debug_coords = [] debug_labels = [] added_obj_labels = [] analysis_labels = [] - labelnames = list(self.count) - pts_mask = self._create_pts_mask(bin_img, labelnames) - final_mask = np.zeros(np.shape(bin_img), np.uint32) debug_img = np.zeros(np.shape(bin_img), np.uint8) - debug_img_duplicates = debug_img.copy() completed_mask_bin, debug_img_removed = _remove_unannotated_objects(pts_mask, bin_img) @@ -229,7 +225,8 @@ def correct_mask(self, bin_img): # Create a new labeled annotation mask to determine number of annotation per object labeled_mask_all, _ = create_labels(mask=completed_mask_bin) masked_image2 = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') - keep_object_ids, keep_object_count = np.unique(masked_image2, return_counts=True) + _, keep_object_count = np.unique(masked_image2, return_counts=True) + # Initialize object count object_id_count = 1 # pts in class used for recovering and labeling @@ -238,7 +235,6 @@ def correct_mask(self, bin_img): x = int(x) y = int(y) mask_pixel_value = labeled_mask_all[y, x] - text = str(object_id_count) # Check if current annotation can be resolved to an object in the mask if mask_pixel_value == 0: if params.verbose == True: @@ -246,9 +242,9 @@ def correct_mask(self, bin_img): unrecovered_ids.append(object_id_count) added_obj_labels.append(object_id_count) analysis_labels.append(names) - # Add debug label annotations later - debug_coords.append((x, y)) - debug_labels.append(text) + # Add info to label object IDs in debug img + debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, + object_id_count, (x, y)) # Add the unresolved object to the labeled mask and the debug img debug_img, final_mask, object_id_count = _draw_unresolved_object(debug_img, final_mask, obj_number=object_id_count, coord=(x, y)) if mask_pixel_value > 0: @@ -258,9 +254,8 @@ def correct_mask(self, bin_img): # New object getting added added_obj_labels.append(mask_pixel_value) analysis_labels.append(names) - # Add debug label annotations later - debug_coords.append((x, y)) - debug_labels.append(text) + debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, + object_id_count, (x, y)) # Draw on labeled mask and debug img debug_img, final_mask, object_id_count = _draw_resolved(debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) @@ -270,6 +265,7 @@ def correct_mask(self, bin_img): # Object annotated more than once so find all associated annotations associated_coords = np.where(masked_image2 == mask_pixel_value) associated_coords = tuple(zip(*associated_coords)) + first_coord = (associated_coords[0][1], associated_coords[0][0]) coord_labels = [] # Find all class labels for each annotation for dup_coord in associated_coords: @@ -292,8 +288,8 @@ def correct_mask(self, bin_img): # Add a thicker pixel where unresolved annotation to the debug img cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) # Add debug label annotations later - debug_coords.append((dup_coord[1], dup_coord[0])) - debug_labels.append(str(object_id_count)) + debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, + object_id_count, (dup_coord[1], dup_coord[0])) # Increment object count up so each pixel drawn in labeled mask is unique object_id_count += 1 if len(re) > 1: @@ -313,15 +309,13 @@ def correct_mask(self, bin_img): if np.all(lbl_counts == 1): # If no, Concat with "_" delimiter concat_lbl = "_".join(list(unique_lbls)) + if params.verbose == True: + print("labels getting concatenated to '{0}' at {1}".format(str(concat_lbl), str(first_coord))) # Adding the object added_obj_labels.append(mask_pixel_value) analysis_labels.append(concat_lbl) # Add debug label annotations later - first_coord = (associated_coords[0][1], associated_coords[0][0]) - if params.verbose == True: - print("labels getting concatenated to '{0}' at {1}".format(str(concat_lbl), str(first_coord))) - debug_coords.append(first_coord) - debug_labels.append(str(object_id_count)) + debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, object_id_count, first_coord) # Draw on labeled mask and debug img debug_img, final_mask, object_id_count = _draw_resolved( debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) @@ -335,7 +329,11 @@ def correct_mask(self, bin_img): # Fill in the duplicate object in the labeled mask, replace with pixel annotations final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) ### ADD PIXEL ANNOTATIONS TO FINAL MASK AND TO DEBUG - + for dup_coord in associated_coords: + cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) + debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, + object_id_count, (dup_coord[1], dup_coord[0])) + object_id_count += 1 # Combine and colorize components of the debug image debug_img_duplicates_rgb = _draw_ghost_of_duplicates_removed(debug_img_duplicates) debug_img = colorize_label_img(debug_img) @@ -483,4 +481,31 @@ def _draw_ghost_of_duplicates_removed(dupes_mask): debug_img_duplicates = dilate(dupes_mask, ksize=params.line_thickness+2, i=1) debug_img_duplicates = debug_img_duplicates - dupes_mask debug_img_duplicates = cv2.cvtColor(debug_img_duplicates, cv2.COLOR_GRAY2RGB) - return debug_img_duplicates \ No newline at end of file + return debug_img_duplicates + + +def _add_debug_id(debug_labels_list, debug_coords_list, id, coord): + """Updates the list of IDs and coordinates for labeling things + in the debugging image + + Parameters + ---------- + debug_labels_list : list + list of ID labels for the debug image + debug_coords_list : list + list of coordinates for ID labels in the debug image + id : int + current object ID number + coord : tuple + coordinate resovled to the current object + + Returns + ---------- + debug_labels_list : list + updated corrected mask + debug_coords_list : list + updated list of coordinates for ID labels in the debug image + """ + debug_labels_list.append(str(id)) + debug_coords_list.append(coord) + return debug_labels_list, debug_coords_list From 158a7216714d43f803663675ff69d7319b8bd75a Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 16 Aug 2024 11:46:07 -0500 Subject: [PATCH 129/162] add complex case to final mask and labels things that are double labeled and cannot be resolved will be counted but not measured --- plantcv/annotate/classes.py | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index e06a237..3b3290f 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -321,15 +321,17 @@ def correct_mask(self, bin_img): debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) else: + # e.g. "total", "total", "germinated" is too complex to measure print("The object at {0} was removed for being too complex. It was associated with the following labels: {1}".format(str(first_coord), str(flat))) - # "total", "total", "germinated" is too complex to measure so added_obj_labels.append(mask_pixel_value) # Draw the ghost of objects removed debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) - # Fill in the duplicate object in the labeled mask, replace with pixel annotations + # Fill in the duplicate object in the labeled mask final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - ### ADD PIXEL ANNOTATIONS TO FINAL MASK AND TO DEBUG - for dup_coord in associated_coords: + ### ADD PIXEL ANNOTATIONS TO FINAL MASK AND TO DEBUG ? + for i, dup_coord in enumerate(associated_coords): + final_mask[dup_coord] = object_id_count + analysis_labels.append(coord_labels[i]) cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, object_id_count, (dup_coord[1], dup_coord[0])) @@ -344,9 +346,9 @@ def correct_mask(self, bin_img): cv2.putText(img=debug_img, text=id_label, org=debug_coords[id], fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=params.text_size, color=(150, 150, 150), thickness=(params.text_thickness)) params.debug = debug - # _debug(visual=final_mask, - # filename=os.path.join(params.debug_outdir, - # f"{params.device}_annotation-corrected.png")) + _debug(visual=final_mask, + filename=os.path.join(params.debug_outdir, + f"{params.device}_annotation-corrected.png")) _debug(visual=debug_img, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected-debug.png")) From ecd777d62f51b245e260ddcf5f21e7fa67b1140f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 16 Aug 2024 13:38:30 -0500 Subject: [PATCH 130/162] Update Points.md add lbls param --- docs/Points.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/docs/Points.md b/docs/Points.md index 97fb6a6..eb0ce2f 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -52,13 +52,14 @@ Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it **plantcv.annotate.Points.correct_mask**(*bin_img*) -**returns** corrected_mask, num +**returns** corrected_mask, lbls, num - **Parameters:** - bin_img - binary image, filtered mask image with selected objects - **Returns:** - - corrected_mask - A labeled mask with non-annotated objects filtered out, and unresolvable annotations marked with a single, labeled pixel. + - corrected_mask - A labeled mask with non-annotated objects filtered out, and unresolvable annotations marked with a labeled pixel. + - lbls - A list of class labels ordered the same as the corrected mask object IDs - num - The number of unique objects in the `corrected_mask`. - **Context:** @@ -66,6 +67,7 @@ Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it - Adds a labeled pixel to the corrected mask if an object cannot be resolved for any annotations (false negatives can be counted but cannot have their size measured downstream). - Returns the number of unique objects in the `corrected_mask` which is useful for downstream analysis. - Debug image is a colorized representation of the labeled mask. The "unresolved" annotation replicates are plotted with a radius of `pcv.params.line_thickness` (default = 5). + - Hint: set `pcv.params.text_size=0` to skip ID labeling and instead only plot the annotation coordinate. - **Example use:** - Remove noise from a microscopy image that is otherwise difficult to filter out with traditional computer vision @@ -93,10 +95,10 @@ marker = pcvan.Points(img=img, figsize=(12,6)) marker.import_list(coords=centroid_coords, label="stomata") # Filter the binary mask based on corrected annotations -corrected_mask, num = marker.correct_mask(bin_img=bin_mask) +corrected_mask, lbls, num = marker.correct_mask(bin_img=bin_mask) # Analysis steps here -size_img = pcv.analyze.size(img=img, labeled_mask=corrected_mask, n_labels=num) +size_img = pcv.analyze.size(img=img, labeled_mask=corrected_mask, n_labels=num, label=lbls) ``` **Annotations After Human Corrections** From 0deafea5adf4f45c616d4febf51a9ad4ec546b94 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 16 Aug 2024 14:03:30 -0500 Subject: [PATCH 131/162] minor clarification to docs for Points classes --- docs/Points.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/Points.md b/docs/Points.md index eb0ce2f..0113574 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -104,11 +104,11 @@ size_img = pcv.analyze.size(img=img, labeled_mask=corrected_mask, n_labels=num, ![Screenshot](img/documentation_images/points_correct_mask/annotated_stomata.png) -**Corrected (and [Colorized](https://plantcv.readthedocs.io/en/stable/visualize_colorize_label_img/)) Mask** +**Corrected & Labeled Mask** ![Screenshot](img/documentation_images/points_correct_mask/colorized_label_img.png) -**Size Analysis Image** +**[Size](https://plantcv.readthedocs.io/en/stable/analyze_size/) Analysis Image** ![Screenshot](img/documentation_images/points_correct_mask/shape_img.png) From d6551956e2f843010f42c7e0df5cd8a0354ae769 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 16 Aug 2024 15:56:22 -0500 Subject: [PATCH 132/162] add dupes for more code coverage --- tests/test_annotate_points.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 0220f9c..7a408e2 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -167,6 +167,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): discs = cv2.imread(test_data.pollen_discs, -1) totalpoints1 = [(116, 47), (322, 46), + (322, 48), (364, 109), (286, 152), (266, 174), @@ -183,8 +184,8 @@ def test_plantcv_annotate_points_correct_mask(test_data): (279, 337)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") + counter.import_list(totalpoints1[0], label="dupe") corrected_mask, _, _ = counter.correct_mask(bin_img=allmask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(discs) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) - From aa6eec496eb2314172666909af4c587238d25d83 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 16 Aug 2024 16:06:04 -0500 Subject: [PATCH 133/162] remove unused var --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 3b3290f..bb575e6 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -273,7 +273,7 @@ def correct_mask(self, bin_img): coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] coord_labels.append(coord_class_label) # Is there more than one class label associated with the given object? - re, rep = np.unique(coord_labels, return_counts=True) + re = np.unique(coord_labels) if len(re) == 1: # Labels are duplicated e.g. "total", "total" # Draw the ghost of objects removed From 3c626e18f340d1a20ef342eaca316542b517511e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 16 Aug 2024 16:07:11 -0500 Subject: [PATCH 134/162] using identity comparison with singleton --- plantcv/annotate/classes.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index bb575e6..0b07861 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -237,7 +237,7 @@ def correct_mask(self, bin_img): mask_pixel_value = labeled_mask_all[y, x] # Check if current annotation can be resolved to an object in the mask if mask_pixel_value == 0: - if params.verbose == True: + if params.verbose: print(f"Object could not be resolved at coordinate: x = {x}, y = {y}") unrecovered_ids.append(object_id_count) added_obj_labels.append(object_id_count) @@ -309,7 +309,7 @@ def correct_mask(self, bin_img): if np.all(lbl_counts == 1): # If no, Concat with "_" delimiter concat_lbl = "_".join(list(unique_lbls)) - if params.verbose == True: + if params.verbose: print("labels getting concatenated to '{0}' at {1}".format(str(concat_lbl), str(first_coord))) # Adding the object added_obj_labels.append(mask_pixel_value) From 95d6c9572b3ba7406a8b8d5dedd64485b6930f0f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Fri, 16 Aug 2024 16:14:23 -0500 Subject: [PATCH 135/162] more deepsource things --- plantcv/annotate/classes.py | 29 ++++++++++++++++++++--------- 1 file changed, 20 insertions(+), 9 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 0b07861..546730b 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -286,7 +286,8 @@ def correct_mask(self, bin_img): final_mask[dup_coord] = object_id_count analysis_labels.append(names) # Add a thicker pixel where unresolved annotation to the debug img - cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) + cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, + color=(object_id_count), thickness=-1) # Add debug label annotations later debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, object_id_count, (dup_coord[1], dup_coord[0])) @@ -310,31 +311,40 @@ def correct_mask(self, bin_img): # If no, Concat with "_" delimiter concat_lbl = "_".join(list(unique_lbls)) if params.verbose: - print("labels getting concatenated to '{0}' at {1}".format(str(concat_lbl), str(first_coord))) + print("labels getting concatenated to '{0}' at " + "{1}".format(str(concat_lbl), str(first_coord))) # Adding the object added_obj_labels.append(mask_pixel_value) analysis_labels.append(concat_lbl) # Add debug label annotations later - debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, object_id_count, first_coord) + debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, + object_id_count, first_coord) # Draw on labeled mask and debug img debug_img, final_mask, object_id_count = _draw_resolved( debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) else: - # e.g. "total", "total", "germinated" is too complex to measure - print("The object at {0} was removed for being too complex. It was associated with the following labels: {1}".format(str(first_coord), str(flat))) + # e.g. "total", "total", "germinated" is too complex to measure + if params.verbose: + print("The object at {0} was removed for being too complex. " + "It was associated with the following " + "labels: {1}".format(str(first_coord), str(flat))) added_obj_labels.append(mask_pixel_value) # Draw the ghost of objects removed - debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, + (255), debug_img_duplicates) # Fill in the duplicate object in the labeled mask final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - ### ADD PIXEL ANNOTATIONS TO FINAL MASK AND TO DEBUG ? + # ADD PIXEL ANNOTATIONS TO FINAL MASK AND TO DEBUG ? for i, dup_coord in enumerate(associated_coords): final_mask[dup_coord] = object_id_count analysis_labels.append(coord_labels[i]) - cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, color=(object_id_count), thickness=-1) + cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), + radius=params.line_thickness, color=(object_id_count), + thickness=-1) debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, (dup_coord[1], dup_coord[0])) + object_id_count, + (dup_coord[1], dup_coord[0])) object_id_count += 1 # Combine and colorize components of the debug image debug_img_duplicates_rgb = _draw_ghost_of_duplicates_removed(debug_img_duplicates) @@ -462,6 +472,7 @@ def _draw_resolved(debug_img, final_mask, pre_lbls_mask, mask_pixel_value, obj_n obj_number += 1 return debug_img, final_mask, obj_number + def _draw_ghost_of_duplicates_removed(dupes_mask): """Fitler a binary mask based on annotations. From cd63506c2fa6f32d31952f03e8b2600d77d5d8de Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 19 Aug 2024 11:49:01 -0500 Subject: [PATCH 136/162] change the dupe list in tests --- tests/test_annotate_points.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 7a408e2..0111977 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -182,9 +182,11 @@ def test_plantcv_annotate_points_correct_mask(test_data): (242, 340), (247, 281), (279, 337)] + dupe_pt = [(116, 47)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") - counter.import_list(totalpoints1[0], label="dupe") + #counter.import_list(totalpoints1[0], label="dupe") + counter.import_list(dupe_pt, label="dupe") corrected_mask, _, _ = counter.correct_mask(bin_img=allmask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(discs) From b816526a6f91fca122d4f3627ccf35e2010dfa27 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 19 Aug 2024 11:57:42 -0500 Subject: [PATCH 137/162] update test coord for more testing coverage --- tests/test_annotate_points.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 0111977..2171894 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -167,7 +167,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): discs = cv2.imread(test_data.pollen_discs, -1) totalpoints1 = [(116, 47), (322, 46), - (322, 48), + (322, 47), (364, 109), (286, 152), (266, 174), @@ -182,7 +182,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): (242, 340), (247, 281), (279, 337)] - dupe_pt = [(116, 47)] + dupe_pt = [(116, 46)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") #counter.import_list(totalpoints1[0], label="dupe") From 22787edfccda86586b69248a5c29c959869cd5b4 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 19 Aug 2024 14:20:04 -0500 Subject: [PATCH 138/162] x,y, order for import list switch --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 546730b..ba9d7d8 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -95,7 +95,7 @@ class label, by default "default" """ if label not in self.coords: self.coords[label] = [] - for (y, x) in coords: + for (x, y) in coords: self.coords[label].append((x, y)) self.count[label] = len(self.coords[label]) self.view(label=label, color=self.color, view_all=False) From c8d12bef95cad7935fd99a6027f1cc12140ca5f8 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 19 Aug 2024 14:20:18 -0500 Subject: [PATCH 139/162] update coords to handle all if statements? --- tests/test_annotate_points.py | 29 +++++++++-------------------- 1 file changed, 9 insertions(+), 20 deletions(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index 2171894..e620e42 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -165,28 +165,17 @@ def test_plantcv_annotate_points_correct_mask(test_data): # generate fake testing image allmask = cv2.imread(test_data.pollen_all, -1) discs = cv2.imread(test_data.pollen_discs, -1) - totalpoints1 = [(116, 47), - (322, 46), - (322, 47), - (364, 109), - (286, 152), - (266, 174), - (305, 196), - (184, 156), - (162, 185), - (65, 189), - (70, 241), - (100, 299), - (186, 351), - (188, 351), - (242, 340), - (247, 281), - (279, 337)] - dupe_pt = [(116, 46)] + totalpoints1 =totalpoints1 = [(529, 157), + (438, 235), + (394, 268), + (451, 295), + (349, 511), + (277, 525), + (97, 290)] + dupe_pts = [(100, 281), (274, 525)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") - #counter.import_list(totalpoints1[0], label="dupe") - counter.import_list(dupe_pt, label="dupe") + counter.import_list(dupe_pts, label="dupe") corrected_mask, _, _ = counter.correct_mask(bin_img=allmask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(discs) From fe9764cc8e071809a86fc3643766ee535461cb8c Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 19 Aug 2024 14:28:05 -0500 Subject: [PATCH 140/162] deepsource things --- plantcv/annotate/classes.py | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index ba9d7d8..9938598 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -163,7 +163,6 @@ class label, by default "default" for (x, y) in self.coords[self.label]: self.ax.plot(x, y, marker='x', c=self.color) - def _create_pts_mask(self, bin_img, labelnames): """Fitler a binary mask based on annotations. @@ -185,9 +184,8 @@ def _create_pts_mask(self, bin_img, labelnames): y = int(y) # Draw pt annotations onto a blank mask pts_mask = cv2.circle(pts_mask, (x, y), radius=0, color=(255), thickness=-1) - + return pts_mask - def correct_mask(self, bin_img): """Fitler a binary mask and make a labeled mask for analysis. @@ -226,7 +224,6 @@ def correct_mask(self, bin_img): labeled_mask_all, _ = create_labels(mask=completed_mask_bin) masked_image2 = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') _, keep_object_count = np.unique(masked_image2, return_counts=True) - # Initialize object count object_id_count = 1 # pts in class used for recovering and labeling @@ -246,7 +243,10 @@ def correct_mask(self, bin_img): debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, object_id_count, (x, y)) # Add the unresolved object to the labeled mask and the debug img - debug_img, final_mask, object_id_count = _draw_unresolved_object(debug_img, final_mask, obj_number=object_id_count, coord=(x, y)) + debug_img, final_mask, object_id_count = _draw_unresolved_object(debug_img, + final_mask, + obj_number=object_id_count, + coord=(x, y)) if mask_pixel_value > 0: # An object is resolved but check if there are other annotations associated with an object associated_count = keep_object_count[mask_pixel_value] @@ -260,9 +260,9 @@ def correct_mask(self, bin_img): debug_img, final_mask, object_id_count = _draw_resolved(debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) if associated_count > 1: - # Has this object been handled already? + # Has this object been handled already? if mask_pixel_value not in added_obj_labels: - # Object annotated more than once so find all associated annotations + # Object annotated more than once so find all associated annotations associated_coords = np.where(masked_image2 == mask_pixel_value) associated_coords = tuple(zip(*associated_coords)) first_coord = (associated_coords[0][1], associated_coords[0][0]) @@ -277,7 +277,8 @@ def correct_mask(self, bin_img): if len(re) == 1: # Labels are duplicated e.g. "total", "total" # Draw the ghost of objects removed - debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, + (255), debug_img_duplicates) # Fill in the duplicate object in the labeled mask, replace with pixel annotations final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) added_obj_labels.append(mask_pixel_value) @@ -299,7 +300,7 @@ def correct_mask(self, bin_img): # Split on "_" in case something has already been combined for lbls in coord_labels: list_lbl = [] - for lbl in lbls: + for lbl in lbls: list_lbl.append(lbl.split("_")) splitup.append(np.concatenate(list_lbl)) # Flatten list of labels @@ -438,7 +439,6 @@ def _draw_unresolved_object(debug_img, final_mask, obj_number, coord): obj_number += 1 return debug_img, final_mask, obj_number - def _draw_resolved(debug_img, final_mask, pre_lbls_mask, mask_pixel_value, obj_number): """Draw resolved/measurable objects @@ -495,8 +495,8 @@ def _draw_ghost_of_duplicates_removed(dupes_mask): debug_img_duplicates = debug_img_duplicates - dupes_mask debug_img_duplicates = cv2.cvtColor(debug_img_duplicates, cv2.COLOR_GRAY2RGB) return debug_img_duplicates - - + + def _add_debug_id(debug_labels_list, debug_coords_list, id, coord): """Updates the list of IDs and coordinates for labeling things in the debugging image @@ -508,7 +508,7 @@ def _add_debug_id(debug_labels_list, debug_coords_list, id, coord): debug_coords_list : list list of coordinates for ID labels in the debug image id : int - current object ID number + current object ID number coord : tuple coordinate resovled to the current object From 3b8b41eaa3441372b5407057f307853aa1809d27 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 19 Aug 2024 14:34:43 -0500 Subject: [PATCH 141/162] add "unresolvable" point for unit test --- tests/test_annotate_points.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index e620e42..ca2b98a 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -171,7 +171,8 @@ def test_plantcv_annotate_points_correct_mask(test_data): (451, 295), (349, 511), (277, 525), - (97, 290)] + (97, 290), + (3,3)] dupe_pts = [(100, 281), (274, 525)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") From acb458bcc9eda5e3fc6302167a99ea5484ca0334 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 19 Aug 2024 14:40:40 -0500 Subject: [PATCH 142/162] Bad indentation detected PYL-W0311 --- plantcv/annotate/classes.py | 158 ++++++++++++++++++------------------ 1 file changed, 79 insertions(+), 79 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 9938598..e893f4e 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -370,41 +370,41 @@ def correct_mask(self, bin_img): def _remove_unannotated_objects(pts_mask, bin_img): - """Fitler a binary mask based on annotations. - - Parameters - ---------- - pts_mask : numpy.ndarray - binary image, mask with all annotations plotted as pixels - bin_img : numpy.ndarray - binary image, mask to get corrected - - Returns - ---------- - filetered_mask : numpy.ndarray - corrected mask - debug_img_removed : numpy.ndarray - binary mask of objects that were removed - """ - debug_img_removed = cv2.cvtColor(pts_mask.copy(), cv2.COLOR_GRAY2RGB) - - # Create a labeled mask from the input mask - labeled_mask, total_obj_num = create_labels(mask=bin_img) - labeled_mask1 = np.copy(labeled_mask) - # Objects that overlap with one or more annotations get kept - masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') - keep_object_ids = np.unique(masked_image) - - # Fill in objects that are not overlapping with an annotation - for i in range(1, total_obj_num + 1): - if i not in keep_object_ids: - labeled_mask1[np.where(labeled_mask == i)] = 0 - debug_img_removed[np.where(labeled_mask == i)] = (50, 50, 50) - - # Create new binary mask after filtering un-annotated objects - completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) - - return completed_mask_bin, debug_img_removed + """Fitler a binary mask based on annotations. + + Parameters + ---------- + pts_mask : numpy.ndarray + binary image, mask with all annotations plotted as pixels + bin_img : numpy.ndarray + binary image, mask to get corrected + + Returns + ---------- + filetered_mask : numpy.ndarray + corrected mask + debug_img_removed : numpy.ndarray + binary mask of objects that were removed + """ + debug_img_removed = cv2.cvtColor(pts_mask.copy(), cv2.COLOR_GRAY2RGB) + + # Create a labeled mask from the input mask + labeled_mask, total_obj_num = create_labels(mask=bin_img) + labeled_mask1 = np.copy(labeled_mask) + # Objects that overlap with one or more annotations get kept + masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') + keep_object_ids = np.unique(masked_image) + + # Fill in objects that are not overlapping with an annotation + for i in range(1, total_obj_num + 1): + if i not in keep_object_ids: + labeled_mask1[np.where(labeled_mask == i)] = 0 + debug_img_removed[np.where(labeled_mask == i)] = (50, 50, 50) + + # Create new binary mask after filtering un-annotated objects + completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) + + return completed_mask_bin, debug_img_removed def _draw_unresolved_object(debug_img, final_mask, obj_number, coord): @@ -474,51 +474,51 @@ def _draw_resolved(debug_img, final_mask, pre_lbls_mask, mask_pixel_value, obj_n def _draw_ghost_of_duplicates_removed(dupes_mask): - """Fitler a binary mask based on annotations. - - Parameters - ---------- - dupes_mask : numpy.ndarray - binary image, mask with all removed (because duplicate annotations) objects - removed_mask : numpy.ndarray - binary image, mask of unannotated and removed objects - - Returns - ---------- - removed_mask : numpy.ndarray - combined mask with all removed objects for debug visualization - """ - from plantcv.plantcv import dilate + """Fitler a binary mask based on annotations. + + Parameters + ---------- + dupes_mask : numpy.ndarray + binary image, mask with all removed (because duplicate annotations) objects + removed_mask : numpy.ndarray + binary image, mask of unannotated and removed objects + + Returns + ---------- + removed_mask : numpy.ndarray + combined mask with all removed objects for debug visualization + """ + from plantcv.plantcv import dilate - # Dilate duplicate objs and subtract the object itself to leave just a halo around - debug_img_duplicates = dilate(dupes_mask, ksize=params.line_thickness+2, i=1) - debug_img_duplicates = debug_img_duplicates - dupes_mask - debug_img_duplicates = cv2.cvtColor(debug_img_duplicates, cv2.COLOR_GRAY2RGB) - return debug_img_duplicates + # Dilate duplicate objs and subtract the object itself to leave just a halo around + debug_img_duplicates = dilate(dupes_mask, ksize=params.line_thickness+2, i=1) + debug_img_duplicates = debug_img_duplicates - dupes_mask + debug_img_duplicates = cv2.cvtColor(debug_img_duplicates, cv2.COLOR_GRAY2RGB) + return debug_img_duplicates def _add_debug_id(debug_labels_list, debug_coords_list, id, coord): - """Updates the list of IDs and coordinates for labeling things - in the debugging image - - Parameters - ---------- - debug_labels_list : list - list of ID labels for the debug image - debug_coords_list : list - list of coordinates for ID labels in the debug image - id : int - current object ID number - coord : tuple - coordinate resovled to the current object - - Returns - ---------- - debug_labels_list : list - updated corrected mask - debug_coords_list : list - updated list of coordinates for ID labels in the debug image - """ - debug_labels_list.append(str(id)) - debug_coords_list.append(coord) - return debug_labels_list, debug_coords_list + """Updates the list of IDs and coordinates for labeling things + in the debugging image + + Parameters + ---------- + debug_labels_list : list + list of ID labels for the debug image + debug_coords_list : list + list of coordinates for ID labels in the debug image + id : int + current object ID number + coord : tuple + coordinate resovled to the current object + + Returns + ---------- + debug_labels_list : list + updated corrected mask + debug_coords_list : list + updated list of coordinates for ID labels in the debug image + """ + debug_labels_list.append(str(id)) + debug_coords_list.append(coord) + return debug_labels_list, debug_coords_list From c48650bf674abd56c2bcf3bee404ee8764c9908f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Mon, 19 Aug 2024 16:20:18 -0500 Subject: [PATCH 143/162] update warning to fstring --- plantcv/annotate/classes.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index e893f4e..0e9a287 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -307,6 +307,7 @@ def correct_mask(self, bin_img): flat = np.concatenate(splitup, dtype=' Date: Mon, 19 Aug 2024 16:25:00 -0500 Subject: [PATCH 144/162] other fstring --- plantcv/annotate/classes.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 0e9a287..ad3717f 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -313,8 +313,8 @@ def correct_mask(self, bin_img): # If no, Concat with "_" delimiter concat_lbl = "_".join(list(unique_lbls)) if params.verbose: - print("labels getting concatenated to '{0}' at " - "{1}".format(str(concat_lbl), str(first_coord))) + print(f"labels getting concatenated to '{concat_lbl}' at " + "{first_coord}") # Adding the object added_obj_labels.append(mask_pixel_value) analysis_labels.append(concat_lbl) From 3b0fd0f940a670857ce2272017af28da0e98df20 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 20 Aug 2024 09:58:32 -0500 Subject: [PATCH 145/162] update correct_mask method to accept labeled mask watershed can be used upstream to separate conjoined things --- plantcv/annotate/classes.py | 30 ++++++++++++++++++++---------- 1 file changed, 20 insertions(+), 10 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index ad3717f..73795cd 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -187,18 +187,20 @@ def _create_pts_mask(self, bin_img, labelnames): return pts_mask - def correct_mask(self, bin_img): + def correct_mask(self, mask): """Fitler a binary mask and make a labeled mask for analysis. Parameters ---------- - bin_img : numpy.ndarray - binary image, mask to get corrected + mask : numpy.ndarray + binary image or labeled mask, mask to get corrected Returns ---------- final_mask : numpy.ndarray corrected and labeled mask with recovered and removed objects + analysis_labels : list + list of analysis labels in the same order of the objects in the final_mask num : int number of objects represented within the labeled mask """ @@ -213,17 +215,24 @@ def correct_mask(self, bin_img): added_obj_labels = [] analysis_labels = [] labelnames = list(self.count) - pts_mask = self._create_pts_mask(bin_img, labelnames) - final_mask = np.zeros(np.shape(bin_img), np.uint32) - debug_img = np.zeros(np.shape(bin_img), np.uint8) + pts_mask = self._create_pts_mask(mask, labelnames) + final_mask = np.zeros(np.shape(mask), np.uint32) + debug_img = np.zeros(np.shape(mask), np.uint8) debug_img_duplicates = debug_img.copy() - completed_mask_bin, debug_img_removed = _remove_unannotated_objects(pts_mask, bin_img) + bin_mask = np.where(mask < 0, 255, 0).astype(np.uint8) + completed_mask_bin, debug_img_removed = _remove_unannotated_objects(pts_mask, bin_mask) + # Make labeled mask if the input mask is binary + input_type = len(np.unique(mask)) + if input_type == 2: + labeled_mask_all, _ = create_labels(mask=completed_mask_bin) + if input_type > 2: + labeled_mask_all = np.copy(mask) # Create a new labeled annotation mask to determine number of annotation per object - labeled_mask_all, _ = create_labels(mask=completed_mask_bin) masked_image2 = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') - _, keep_object_count = np.unique(masked_image2, return_counts=True) + keep_pixel_vals, keep_object_count = np.unique(masked_image2, return_counts=True) + print(keep_object_count) # Initialize object count object_id_count = 1 # pts in class used for recovering and labeling @@ -249,7 +258,8 @@ def correct_mask(self, bin_img): coord=(x, y)) if mask_pixel_value > 0: # An object is resolved but check if there are other annotations associated with an object - associated_count = keep_object_count[mask_pixel_value] + mask_pixel_index = np.where(keep_pixel_vals == mask_pixel_value)[0] + associated_count = keep_object_count[mask_pixel_index] if associated_count == 1: # New object getting added added_obj_labels.append(mask_pixel_value) From 07a61ede9e2db33152bb9c8508f1d31601721641 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 20 Aug 2024 09:58:49 -0500 Subject: [PATCH 146/162] add a test for the labeled mask case --- tests/test_annotate_points.py | 12 +++++++++++- 1 file changed, 11 insertions(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index ca2b98a..f30fad0 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -178,6 +178,16 @@ def test_plantcv_annotate_points_correct_mask(test_data): counter.import_list(totalpoints1, label="total") counter.import_list(dupe_pts, label="dupe") - corrected_mask, _, _ = counter.correct_mask(bin_img=allmask) + corrected_mask, _, _ = counter.correct_mask(mask=allmask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(discs) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) + +def test_plantcv_annotate_points_correct_mask_labeled(test_data): + """Test for PlantCV.""" + lbl_mask = cv2.imread(test_data.kmeans_seed_gray_img, -1) + dupe_pts = [(100, 281), (274, 525)] + counter = Points(np.copy(lbl_mask), figsize=(8, 6)) + counter.import_list(dupe_pts, label="total") + corrected_mask, _, _ = counter.correct_mask(mask=lbl_mask) + assert np.count_nonzero(corrected_mask) < np.count_nonzero(lbl_mask) + From d1aea5d2aab5892a52e4b2d7f0eaf0743fc00867 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 20 Aug 2024 10:50:07 -0500 Subject: [PATCH 147/162] update _remove_unannotated_objects to be the place where bin vs labeled mask is handled --- plantcv/annotate/classes.py | 58 +++++++++++++++++-------------------- 1 file changed, 26 insertions(+), 32 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 73795cd..c486f01 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -117,7 +117,7 @@ def import_file(self, filename): for key in keys: keycoor = coords[key] - keycoor = list(map(lambda sub: (sub[1], sub[0]), keycoor)) + keycoor = list(map(lambda sub: (sub[0], sub[1]), keycoor)) self.import_list(keycoor, label=key) def view(self, label="default", color="r", view_all=False): @@ -163,20 +163,20 @@ class label, by default "default" for (x, y) in self.coords[self.label]: self.ax.plot(x, y, marker='x', c=self.color) - def _create_pts_mask(self, bin_img, labelnames): + def _create_pts_mask(self, mask, labelnames): """Fitler a binary mask based on annotations. Parameters ---------- - bin_img : numpy.ndarray - binary image + mask : numpy.ndarray + mask for image size Returns ---------- pts_mask : numpy.ndarray binary mask of annotations """ - pts_mask = np.zeros(np.shape(bin_img), np.uint8) + pts_mask = np.zeros(np.shape(mask), np.uint8) # Create points mask from all annotations for names in labelnames: for (x, y) in self.coords[names]: @@ -215,24 +215,17 @@ def correct_mask(self, mask): added_obj_labels = [] analysis_labels = [] labelnames = list(self.count) - pts_mask = self._create_pts_mask(mask, labelnames) final_mask = np.zeros(np.shape(mask), np.uint32) debug_img = np.zeros(np.shape(mask), np.uint8) debug_img_duplicates = debug_img.copy() - bin_mask = np.where(mask < 0, 255, 0).astype(np.uint8) - completed_mask_bin, debug_img_removed = _remove_unannotated_objects(pts_mask, bin_mask) + bin_mask = np.where(mask > 0, 255, 0).astype(np.uint8) + pts_mask = self._create_pts_mask(bin_mask, labelnames) + labeled_mask_all, debug_img_removed = _remove_unannotated_objects(pts_mask, mask) - # Make labeled mask if the input mask is binary - input_type = len(np.unique(mask)) - if input_type == 2: - labeled_mask_all, _ = create_labels(mask=completed_mask_bin) - if input_type > 2: - labeled_mask_all = np.copy(mask) # Create a new labeled annotation mask to determine number of annotation per object masked_image2 = apply_mask(img=labeled_mask_all, mask=pts_mask, mask_color='black') keep_pixel_vals, keep_object_count = np.unique(masked_image2, return_counts=True) - print(keep_object_count) # Initialize object count object_id_count = 1 # pts in class used for recovering and labeling @@ -323,8 +316,7 @@ def correct_mask(self, mask): # If no, Concat with "_" delimiter concat_lbl = "_".join(list(unique_lbls)) if params.verbose: - print(f"labels getting concatenated to '{concat_lbl}' at " - "{first_coord}") + print(f"labels getting concatenated to '{concat_lbl}' at {first_coord}") # Adding the object added_obj_labels.append(mask_pixel_value) analysis_labels.append(concat_lbl) @@ -380,15 +372,15 @@ def correct_mask(self, mask): return final_mask, analysis_labels, num -def _remove_unannotated_objects(pts_mask, bin_img): - """Fitler a binary mask based on annotations. +def _remove_unannotated_objects(pts_mask, mask): + """Fitler a mask based on annotations, handles both binary and labeled masks. Parameters ---------- pts_mask : numpy.ndarray binary image, mask with all annotations plotted as pixels - bin_img : numpy.ndarray - binary image, mask to get corrected + mask : numpy.ndarray + input mask image, mask to get corrected Returns ---------- @@ -397,25 +389,27 @@ def _remove_unannotated_objects(pts_mask, bin_img): debug_img_removed : numpy.ndarray binary mask of objects that were removed """ + from plantcv import plantcv as pcv debug_img_removed = cv2.cvtColor(pts_mask.copy(), cv2.COLOR_GRAY2RGB) - + # Create a labeled mask from the input mask - labeled_mask, total_obj_num = create_labels(mask=bin_img) - labeled_mask1 = np.copy(labeled_mask) + input_type = len(np.unique(mask)) + if input_type == 2: + labeled_mask, total_obj_num = create_labels(mask=mask) + if input_type > 2: + labeled_mask = np.copy(mask) + total_obj_num = input_type # Objects that overlap with one or more annotations get kept - masked_image = apply_mask(img=labeled_mask1, mask=pts_mask, mask_color='black') + masked_image = apply_mask(img=labeled_mask, mask=pts_mask, mask_color='black') keep_object_ids = np.unique(masked_image) - + # Fill in objects that are not overlapping with an annotation for i in range(1, total_obj_num + 1): if i not in keep_object_ids: - labeled_mask1[np.where(labeled_mask == i)] = 0 + labeled_mask[np.where(labeled_mask == i)] = 0 debug_img_removed[np.where(labeled_mask == i)] = (50, 50, 50) - - # Create new binary mask after filtering un-annotated objects - completed_mask_bin = np.where(labeled_mask1 > 0, 255, 0) - - return completed_mask_bin, debug_img_removed + + return labeled_mask, debug_img_removed def _draw_unresolved_object(debug_img, final_mask, obj_number, coord): From 750f8bdfc9f82c9c596c77988eadef09e086e1fe Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 20 Aug 2024 10:56:15 -0500 Subject: [PATCH 148/162] update Points.md with new param name --- docs/Points.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/Points.md b/docs/Points.md index 0113574..db17d90 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -50,12 +50,12 @@ roi = pcv.roi.custom(img=img, vertices=marker.coords['default']) Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it is possible to interactively click to collect coordinates from an image, then use these coordinate to remove and recover objects from a binary mask. -**plantcv.annotate.Points.correct_mask**(*bin_img*) +**plantcv.annotate.Points.correct_mask**(*mask*) **returns** corrected_mask, lbls, num - **Parameters:** - - bin_img - binary image, filtered mask image with selected objects + - mask - binary or labeled mask image, filtered mask image with selected objects, or the output from [`plantcv.watershed`](https://plantcv.readthedocs.io/en/stable/watershed/) - **Returns:** - corrected_mask - A labeled mask with non-annotated objects filtered out, and unresolvable annotations marked with a labeled pixel. @@ -95,7 +95,7 @@ marker = pcvan.Points(img=img, figsize=(12,6)) marker.import_list(coords=centroid_coords, label="stomata") # Filter the binary mask based on corrected annotations -corrected_mask, lbls, num = marker.correct_mask(bin_img=bin_mask) +corrected_mask, lbls, num = marker.correct_mask(mask=bin_mask) # Analysis steps here size_img = pcv.analyze.size(img=img, labeled_mask=corrected_mask, n_labels=num, label=lbls) From 679061c287ebf0a4cb99ab4b6db07bfcd0287bcc Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 20 Aug 2024 11:07:38 -0500 Subject: [PATCH 149/162] deepsource stuff --- plantcv/annotate/classes.py | 92 ++++++++++++++++++------------------- 1 file changed, 45 insertions(+), 47 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index c486f01..4532062 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -199,7 +199,7 @@ def correct_mask(self, mask): ---------- final_mask : numpy.ndarray corrected and labeled mask with recovered and removed objects - analysis_labels : list + analysis_labels : list list of analysis labels in the same order of the objects in the final_mask num : int number of objects represented within the labeled mask @@ -310,7 +310,6 @@ def correct_mask(self, mask): flat = np.concatenate(splitup, dtype=' 2: labeled_mask = np.copy(mask) @@ -415,26 +412,26 @@ def _remove_unannotated_objects(pts_mask, mask): def _draw_unresolved_object(debug_img, final_mask, obj_number, coord): """Draw unresolved objects as a labeled pixel - Parameters - ---------- - debug_img : numpy.ndarray - debug image of objects, unresolved annotations, etc - final_mask : numpy.ndarray - corrected and labeled mask with recovered and removed objects - obj_number : int - ID number for the current object getting added - coord : tuple - coordinate of the unresolved object annotation + Parameters + ---------- + debug_img : numpy.ndarray + debug image of objects, unresolved annotations, etc + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects + obj_number : int + ID number for the current object getting added + coord : tuple + coordinate of the unresolved object annotation - Returns - ---------- - debug_img : numpy.ndarray - debug image of objects, unresolved annotations, etc - final_mask : numpy.ndarray - corrected and labeled mask with recovered and removed objects - obj_number : int - ID number for the current object getting added - """ + Returns + ---------- + debug_img : numpy.ndarray + debug image of objects, unresolved annotations, etc + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects + obj_number : int + ID number for the current object getting added + """ (x, y) = coord # Add a pixel where unresolved annotation to the mask final_mask[y, x] = obj_number @@ -444,31 +441,32 @@ def _draw_unresolved_object(debug_img, final_mask, obj_number, coord): obj_number += 1 return debug_img, final_mask, obj_number + def _draw_resolved(debug_img, final_mask, pre_lbls_mask, mask_pixel_value, obj_number): """Draw resolved/measurable objects - Parameters - ---------- - debug_img : numpy.ndarray - debug image of objects, unresolved annotations, etc - final_mask : numpy.ndarray - corrected and labeled mask with recovered and removed objects - pre_lbls_mask : numpy.ndarray - labeled mask of all resolvable objects - mask_pixel_value : int - ID number for the current resolved object in pre_lbls_mask - obj_number : int - ID number for the current object getting added + Parameters + ---------- + debug_img : numpy.ndarray + debug image of objects, unresolved annotations, etc + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects + pre_lbls_mask : numpy.ndarray + labeled mask of all resolvable objects + mask_pixel_value : int + ID number for the current resolved object in pre_lbls_mask + obj_number : int + ID number for the current object getting added - Returns - ---------- - debug_img : numpy.ndarray - debug image of objects, unresolved annotations, etc - final_mask : numpy.ndarray - corrected and labeled mask with recovered and removed objects - obj_number : int - ID number for the current object getting added - """ + Returns + ---------- + debug_img : numpy.ndarray + debug image of objects, unresolved annotations, etc + final_mask : numpy.ndarray + corrected and labeled mask with recovered and removed objects + obj_number : int + ID number for the current object getting added + """ # Add a pixel where unresolved annotation to the mask # Draw on labeled mask final_mask = np.where(pre_lbls_mask == mask_pixel_value, obj_number, final_mask) From 532c91bd4dde7c82980402b1c10bfd50a2769ae7 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 20 Aug 2024 11:21:22 -0500 Subject: [PATCH 150/162] stop specifying dtype in np.concat step because deepsource complaint --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 4532062..65c22e0 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -307,7 +307,7 @@ def correct_mask(self, mask): list_lbl.append(lbl.split("_")) splitup.append(np.concatenate(list_lbl)) # Flatten list of labels - flat = np.concatenate(splitup, dtype=' Date: Tue, 20 Aug 2024 11:22:01 -0500 Subject: [PATCH 151/162] remove whitespace --- plantcv/annotate/classes.py | 1 - 1 file changed, 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 65c22e0..0d195b5 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -325,7 +325,6 @@ def correct_mask(self, mask): # Draw on labeled mask and debug img debug_img, final_mask, object_id_count = _draw_resolved( debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) - else: # e.g. "total", "total", "germinated" is too complex to measure if params.verbose: From 52f6aa251412314722db521c87e3775d90f547bd Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 17 Sep 2024 10:29:42 -0500 Subject: [PATCH 152/162] x,y order in import_list revert --- plantcv/annotate/classes.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 0d195b5..f95e645 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -95,7 +95,7 @@ class label, by default "default" """ if label not in self.coords: self.coords[label] = [] - for (x, y) in coords: + for (y, x) in coords: self.coords[label].append((x, y)) self.count[label] = len(self.coords[label]) self.view(label=label, color=self.color, view_all=False) @@ -117,7 +117,7 @@ def import_file(self, filename): for key in keys: keycoor = coords[key] - keycoor = list(map(lambda sub: (sub[0], sub[1]), keycoor)) + keycoor = list(map(lambda sub: (sub[1], sub[0]), keycoor)) self.import_list(keycoor, label=key) def view(self, label="default", color="r", view_all=False): From c783cff05aa39bd5b5f3346bdbcff2a54d1e4f42 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Tue, 17 Sep 2024 14:39:41 -0500 Subject: [PATCH 153/162] xy order fix for unit test coverage --- tests/test_annotate_points.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index f30fad0..31a5335 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -165,15 +165,15 @@ def test_plantcv_annotate_points_correct_mask(test_data): # generate fake testing image allmask = cv2.imread(test_data.pollen_all, -1) discs = cv2.imread(test_data.pollen_discs, -1) - totalpoints1 =totalpoints1 = [(529, 157), - (438, 235), - (394, 268), - (451, 295), - (349, 511), - (277, 525), - (97, 290), + totalpoints1 =totalpoints1 = [(157, 529), + (235, 438), + (268, 394), + (295, 451), + (511, 349), + (525, 277), + (290, 97), (3,3)] - dupe_pts = [(100, 281), (274, 525)] + dupe_pts = [(281, 100), (525, 274)] counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") counter.import_list(dupe_pts, label="dupe") @@ -185,7 +185,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): def test_plantcv_annotate_points_correct_mask_labeled(test_data): """Test for PlantCV.""" lbl_mask = cv2.imread(test_data.kmeans_seed_gray_img, -1) - dupe_pts = [(100, 281), (274, 525)] + dupe_pts = [(281, 100), (525, 274)] counter = Points(np.copy(lbl_mask), figsize=(8, 6)) counter.import_list(dupe_pts, label="total") corrected_mask, _, _ = counter.correct_mask(mask=lbl_mask) From 91d996a1ec1db04e48d629aabac6f33efb3af1f9 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 18 Sep 2024 09:38:03 -0500 Subject: [PATCH 154/162] replace print statements with pcv.warn --- plantcv/annotate/classes.py | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index f95e645..9be85c9 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -314,8 +314,7 @@ def correct_mask(self, mask): if np.all(lbl_counts == 1): # If no, Concat with "_" delimiter concat_lbl = "_".join(list(unique_lbls)) - if params.verbose: - print(f"labels getting concatenated to '{concat_lbl}' at {first_coord}") + warn(f"labels getting concatenated to '{concat_lbl}' at {first_coord}") # Adding the object added_obj_labels.append(mask_pixel_value) analysis_labels.append(concat_lbl) @@ -327,10 +326,8 @@ def correct_mask(self, mask): debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) else: # e.g. "total", "total", "germinated" is too complex to measure - if params.verbose: - print(f"The object at {first_coord} was removed for being too complex. " - "It was associated with the following " - "labels: {flat1}") + warn(f"The object at {first_coord} was removed for being too complex. " + "It was associated with the following labels: {flat1}") added_obj_labels.append(mask_pixel_value) # Draw the ghost of objects removed debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, From 5dd79e33ad8243b3dc3dc7af697d0b0977ff8424 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 18 Sep 2024 09:39:25 -0500 Subject: [PATCH 155/162] another instance of pcv.warn & import placement --- plantcv/annotate/classes.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 9be85c9..48446e8 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -8,7 +8,7 @@ from math import floor import matplotlib.pyplot as plt from plantcv.plantcv.annotate.points import _find_closest_pt -from plantcv.plantcv import warn, params +from plantcv.plantcv import warn, params, dilate from plantcv.plantcv._debug import _debug from plantcv.plantcv import create_labels, apply_mask @@ -236,8 +236,7 @@ def correct_mask(self, mask): mask_pixel_value = labeled_mask_all[y, x] # Check if current annotation can be resolved to an object in the mask if mask_pixel_value == 0: - if params.verbose: - print(f"Object could not be resolved at coordinate: x = {x}, y = {y}") + warn(f"Object could not be resolved at coordinate: x = {x}, y = {y}") unrecovered_ids.append(object_id_count) added_obj_labels.append(object_id_count) analysis_labels.append(names) @@ -487,8 +486,6 @@ def _draw_ghost_of_duplicates_removed(dupes_mask): removed_mask : numpy.ndarray combined mask with all removed objects for debug visualization """ - from plantcv.plantcv import dilate - # Dilate duplicate objs and subtract the object itself to leave just a halo around debug_img_duplicates = dilate(dupes_mask, ksize=params.line_thickness+2, i=1) debug_img_duplicates = debug_img_duplicates - dupes_mask From a62ea63d96c8bee83384a985757e992b0d540698 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 18 Sep 2024 09:59:01 -0500 Subject: [PATCH 156/162] indent fix --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 48446e8..9ec32fb 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -326,7 +326,7 @@ def correct_mask(self, mask): else: # e.g. "total", "total", "germinated" is too complex to measure warn(f"The object at {first_coord} was removed for being too complex. " - "It was associated with the following labels: {flat1}") + "It was associated with the following labels: {flat1}") added_obj_labels.append(mask_pixel_value) # Draw the ghost of objects removed debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, From 34d6ceb40834453a434cb6f88c446b48bbbdf4fe Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 18 Sep 2024 10:38:29 -0500 Subject: [PATCH 157/162] change dictionary iteration logic to avoid nested for loops --- plantcv/annotate/classes.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 9ec32fb..618cb85 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -178,12 +178,14 @@ def _create_pts_mask(self, mask, labelnames): """ pts_mask = np.zeros(np.shape(mask), np.uint8) # Create points mask from all annotations - for names in labelnames: - for (x, y) in self.coords[names]: - x = int(x) - y = int(y) - # Draw pt annotations onto a blank mask - pts_mask = cv2.circle(pts_mask, (x, y), radius=0, color=(255), thickness=-1) + pts = [] + for i in self.coords.values(): + if i: + pts.extend(i) + for pt in pts: + (x, y) = pt + # Draw pt annotations onto a blank mask + pts_mask = cv2.circle(pts_mask, (int(x), int(y)), radius=0, color=(255), thickness=-1) return pts_mask From a980fe54bec8a0c86cbb08a696cec60826ed62ea Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 18 Sep 2024 11:18:23 -0500 Subject: [PATCH 158/162] different approach to dec complexity? --- plantcv/annotate/classes.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 618cb85..545231e 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -178,11 +178,8 @@ def _create_pts_mask(self, mask, labelnames): """ pts_mask = np.zeros(np.shape(mask), np.uint8) # Create points mask from all annotations - pts = [] - for i in self.coords.values(): - if i: - pts.extend(i) - for pt in pts: + pts_all = sum((pt for pts in self.coords.values() for pt in self.coords.values()), []) + for pt in pts_all: (x, y) = pt # Draw pt annotations onto a blank mask pts_mask = cv2.circle(pts_mask, (int(x), int(y)), radius=0, color=(255), thickness=-1) From 08e14bc52c03579abacf44219505a063402f1533 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 18 Sep 2024 14:06:07 -0500 Subject: [PATCH 159/162] simplify sum syntax --- plantcv/annotate/classes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 545231e..396a97e 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -178,7 +178,7 @@ def _create_pts_mask(self, mask, labelnames): """ pts_mask = np.zeros(np.shape(mask), np.uint8) # Create points mask from all annotations - pts_all = sum((pt for pts in self.coords.values() for pt in self.coords.values()), []) + pts_all = sum(self.coords.values(), []) for pt in pts_all: (x, y) = pt # Draw pt annotations onto a blank mask From e75780698bd544d79b2513acc2d41453b20305c7 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 18 Sep 2024 15:33:28 -0500 Subject: [PATCH 160/162] refactor looping method in correct_mask --- plantcv/annotate/classes.py | 215 ++++++++++++++++++------------------ 1 file changed, 110 insertions(+), 105 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 396a97e..1e83501 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -217,6 +217,11 @@ def correct_mask(self, mask): final_mask = np.zeros(np.shape(mask), np.uint32) debug_img = np.zeros(np.shape(mask), np.uint8) debug_img_duplicates = debug_img.copy() + pts_all = sum(self.coords.values(), []) + labels_all = [] + for pt in pts_all: + coord_class_label = [k for k, v in self.coords.items() if pt in v] + labels_all.append(coord_class_label) bin_mask = np.where(mask > 0, 255, 0).astype(np.uint8) pts_mask = self._create_pts_mask(bin_mask, labelnames) @@ -228,121 +233,121 @@ def correct_mask(self, mask): # Initialize object count object_id_count = 1 # pts in class used for recovering and labeling - for names in labelnames: - for (x, y) in self.coords[names]: - x = int(x) - y = int(y) - mask_pixel_value = labeled_mask_all[y, x] - # Check if current annotation can be resolved to an object in the mask - if mask_pixel_value == 0: - warn(f"Object could not be resolved at coordinate: x = {x}, y = {y}") - unrecovered_ids.append(object_id_count) - added_obj_labels.append(object_id_count) + for p, current_pt in enumerate(pts_all): + x = int(current_pt[1]) + y = int(current_pt[0]) + names = labels_all[p] + mask_pixel_value = labeled_mask_all[y, x] + # Check if current annotation can be resolved to an object in the mask + if mask_pixel_value == 0: + warn(f"Object could not be resolved at coordinate: x = {x}, y = {y}") + unrecovered_ids.append(object_id_count) + added_obj_labels.append(object_id_count) + analysis_labels.append(names) + # Add info to label object IDs in debug img + debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, + object_id_count, (x, y)) + # Add the unresolved object to the labeled mask and the debug img + debug_img, final_mask, object_id_count = _draw_unresolved_object(debug_img, + final_mask, + obj_number=object_id_count, + coord=(x, y)) + if mask_pixel_value > 0: + # An object is resolved but check if there are other annotations associated with an object + mask_pixel_index = np.where(keep_pixel_vals == mask_pixel_value)[0] + associated_count = keep_object_count[mask_pixel_index] + if associated_count == 1: + # New object getting added + added_obj_labels.append(mask_pixel_value) analysis_labels.append(names) - # Add info to label object IDs in debug img debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, (x, y)) - # Add the unresolved object to the labeled mask and the debug img - debug_img, final_mask, object_id_count = _draw_unresolved_object(debug_img, - final_mask, - obj_number=object_id_count, - coord=(x, y)) - if mask_pixel_value > 0: - # An object is resolved but check if there are other annotations associated with an object - mask_pixel_index = np.where(keep_pixel_vals == mask_pixel_value)[0] - associated_count = keep_object_count[mask_pixel_index] - if associated_count == 1: - # New object getting added - added_obj_labels.append(mask_pixel_value) - analysis_labels.append(names) - debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, (x, y)) - # Draw on labeled mask and debug img - debug_img, final_mask, object_id_count = _draw_resolved(debug_img, final_mask, labeled_mask_all, - mask_pixel_value, object_id_count) - if associated_count > 1: - # Has this object been handled already? - if mask_pixel_value not in added_obj_labels: - # Object annotated more than once so find all associated annotations - associated_coords = np.where(masked_image2 == mask_pixel_value) - associated_coords = tuple(zip(*associated_coords)) - first_coord = (associated_coords[0][1], associated_coords[0][0]) - coord_labels = [] - # Find all class labels for each annotation + object_id_count, (x, y)) + # Draw on labeled mask and debug img + debug_img, final_mask, object_id_count = _draw_resolved(debug_img, final_mask, labeled_mask_all, + mask_pixel_value, object_id_count) + if associated_count > 1: + # Has this object been handled already? + if mask_pixel_value not in added_obj_labels: + # Object annotated more than once so find all associated annotations + associated_coords = np.where(masked_image2 == mask_pixel_value) + associated_coords = tuple(zip(*associated_coords)) + first_coord = (associated_coords[0][1], associated_coords[0][0]) + coord_labels = [] + # Find all class labels for each annotation + for dup_coord in associated_coords: + # Flip x & y for numpy, and find the associated class label with each coordinate + coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] + coord_labels.append(coord_class_label) + # Is there more than one class label associated with the given object? + re = np.unique(coord_labels) + if len(re) == 1: + # Labels are duplicated e.g. "total", "total" + # Draw the ghost of objects removed + debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, + (255), debug_img_duplicates) + # Fill in the duplicate object in the labeled mask, replace with pixel annotations + final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) + added_obj_labels.append(mask_pixel_value) for dup_coord in associated_coords: - # Flip x & y for numpy, and find the associated class label with each coordinate - coord_class_label = [k for k, v in self.coords.items() if (dup_coord[1], dup_coord[0]) in v] - coord_labels.append(coord_class_label) - # Is there more than one class label associated with the given object? - re = np.unique(coord_labels) - if len(re) == 1: - # Labels are duplicated e.g. "total", "total" + # Draw each pixel in the final mask + final_mask[dup_coord] = object_id_count + analysis_labels.append(names) + # Add a thicker pixel where unresolved annotation to the debug img + cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, + color=(object_id_count), thickness=-1) + # Add debug label annotations later + debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, + object_id_count, (dup_coord[1], dup_coord[0])) + # Increment object count up so each pixel drawn in labeled mask is unique + object_id_count += 1 + if len(re) > 1: + # More than one class label associated with a given object + splitup = [] + # Split on "_" in case something has already been combined + for lbls in coord_labels: + list_lbl = [] + for lbl in lbls: + list_lbl.append(lbl.split("_")) + splitup.append(np.concatenate(list_lbl)) + # Flatten list of labels + flat = np.concatenate(splitup) + # Grab each unique label from the list + unique_lbls, lbl_counts = np.unique(flat, return_counts=True) + # Is there duplication within each class label for the given object? + if np.all(lbl_counts == 1): + # If no, Concat with "_" delimiter + concat_lbl = "_".join(list(unique_lbls)) + warn(f"labels getting concatenated to '{concat_lbl}' at {first_coord}") + # Adding the object + added_obj_labels.append(mask_pixel_value) + analysis_labels.append(concat_lbl) + # Add debug label annotations later + debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, + object_id_count, first_coord) + # Draw on labeled mask and debug img + debug_img, final_mask, object_id_count = _draw_resolved( + debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) + else: + # e.g. "total", "total", "germinated" is too complex to measure + warn(f"The object at {first_coord} was removed for being too complex. " + "It was associated with the following labels: {flat1}") + added_obj_labels.append(mask_pixel_value) # Draw the ghost of objects removed debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, (255), debug_img_duplicates) - # Fill in the duplicate object in the labeled mask, replace with pixel annotations + # Fill in the duplicate object in the labeled mask final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - added_obj_labels.append(mask_pixel_value) - for dup_coord in associated_coords: - # Draw each pixel in the final mask + # ADD PIXEL ANNOTATIONS TO FINAL MASK AND TO DEBUG ? + for i, dup_coord in enumerate(associated_coords): final_mask[dup_coord] = object_id_count - analysis_labels.append(names) - # Add a thicker pixel where unresolved annotation to the debug img - cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, - color=(object_id_count), thickness=-1) - # Add debug label annotations later + analysis_labels.append(coord_labels[i]) + cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), + radius=params.line_thickness, color=(object_id_count), + thickness=-1) debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, (dup_coord[1], dup_coord[0])) - # Increment object count up so each pixel drawn in labeled mask is unique + object_id_count, + (dup_coord[1], dup_coord[0])) object_id_count += 1 - if len(re) > 1: - # More than one class label associated with a given object - splitup = [] - # Split on "_" in case something has already been combined - for lbls in coord_labels: - list_lbl = [] - for lbl in lbls: - list_lbl.append(lbl.split("_")) - splitup.append(np.concatenate(list_lbl)) - # Flatten list of labels - flat = np.concatenate(splitup) - # Grab each unique label from the list - unique_lbls, lbl_counts = np.unique(flat, return_counts=True) - # Is there duplication within each class label for the given object? - if np.all(lbl_counts == 1): - # If no, Concat with "_" delimiter - concat_lbl = "_".join(list(unique_lbls)) - warn(f"labels getting concatenated to '{concat_lbl}' at {first_coord}") - # Adding the object - added_obj_labels.append(mask_pixel_value) - analysis_labels.append(concat_lbl) - # Add debug label annotations later - debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, first_coord) - # Draw on labeled mask and debug img - debug_img, final_mask, object_id_count = _draw_resolved( - debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) - else: - # e.g. "total", "total", "germinated" is too complex to measure - warn(f"The object at {first_coord} was removed for being too complex. " - "It was associated with the following labels: {flat1}") - added_obj_labels.append(mask_pixel_value) - # Draw the ghost of objects removed - debug_img_duplicates = np.where(labeled_mask_all == mask_pixel_value, - (255), debug_img_duplicates) - # Fill in the duplicate object in the labeled mask - final_mask = np.where(labeled_mask_all == mask_pixel_value, (0), final_mask) - # ADD PIXEL ANNOTATIONS TO FINAL MASK AND TO DEBUG ? - for i, dup_coord in enumerate(associated_coords): - final_mask[dup_coord] = object_id_count - analysis_labels.append(coord_labels[i]) - cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), - radius=params.line_thickness, color=(object_id_count), - thickness=-1) - debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, - (dup_coord[1], dup_coord[0])) - object_id_count += 1 # Combine and colorize components of the debug image debug_img_duplicates_rgb = _draw_ghost_of_duplicates_removed(debug_img_duplicates) debug_img = colorize_label_img(debug_img) From 05a67563f833b8fba6c8691ca8ae27632bd7fb9f Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 18 Sep 2024 15:45:32 -0500 Subject: [PATCH 161/162] fix x & y order given new looping method --- plantcv/annotate/classes.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 1e83501..26dfffa 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -234,8 +234,8 @@ def correct_mask(self, mask): object_id_count = 1 # pts in class used for recovering and labeling for p, current_pt in enumerate(pts_all): - x = int(current_pt[1]) - y = int(current_pt[0]) + x = int(current_pt[0]) + y = int(current_pt[1]) names = labels_all[p] mask_pixel_value = labeled_mask_all[y, x] # Check if current annotation can be resolved to an object in the mask From 70474fcd7f8f223cebf4eb698bd4c99e4c932b6e Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Wed, 18 Sep 2024 16:00:46 -0500 Subject: [PATCH 162/162] whitespace and indent fixes --- plantcv/annotate/classes.py | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index 26dfffa..c5b5a78 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -218,7 +218,7 @@ def correct_mask(self, mask): debug_img = np.zeros(np.shape(mask), np.uint8) debug_img_duplicates = debug_img.copy() pts_all = sum(self.coords.values(), []) - labels_all = [] + labels_all = [] for pt in pts_all: coord_class_label = [k for k, v in self.coords.items() if pt in v] labels_all.append(coord_class_label) @@ -249,9 +249,9 @@ def correct_mask(self, mask): object_id_count, (x, y)) # Add the unresolved object to the labeled mask and the debug img debug_img, final_mask, object_id_count = _draw_unresolved_object(debug_img, - final_mask, - obj_number=object_id_count, - coord=(x, y)) + final_mask, + obj_number=object_id_count, + coord=(x, y)) if mask_pixel_value > 0: # An object is resolved but check if there are other annotations associated with an object mask_pixel_index = np.where(keep_pixel_vals == mask_pixel_value)[0] @@ -261,7 +261,7 @@ def correct_mask(self, mask): added_obj_labels.append(mask_pixel_value) analysis_labels.append(names) debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, (x, y)) + object_id_count, (x, y)) # Draw on labeled mask and debug img debug_img, final_mask, object_id_count = _draw_resolved(debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) @@ -294,10 +294,10 @@ def correct_mask(self, mask): analysis_labels.append(names) # Add a thicker pixel where unresolved annotation to the debug img cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), radius=params.line_thickness, - color=(object_id_count), thickness=-1) + color=(object_id_count), thickness=-1) # Add debug label annotations later debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, (dup_coord[1], dup_coord[0])) + object_id_count, (dup_coord[1], dup_coord[0])) # Increment object count up so each pixel drawn in labeled mask is unique object_id_count += 1 if len(re) > 1: @@ -323,7 +323,7 @@ def correct_mask(self, mask): analysis_labels.append(concat_lbl) # Add debug label annotations later debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, first_coord) + object_id_count, first_coord) # Draw on labeled mask and debug img debug_img, final_mask, object_id_count = _draw_resolved( debug_img, final_mask, labeled_mask_all, mask_pixel_value, object_id_count) @@ -342,11 +342,11 @@ def correct_mask(self, mask): final_mask[dup_coord] = object_id_count analysis_labels.append(coord_labels[i]) cv2.circle(debug_img, (dup_coord[1], dup_coord[0]), - radius=params.line_thickness, color=(object_id_count), - thickness=-1) + radius=params.line_thickness, color=(object_id_count), + thickness=-1) debug_labels, debug_coords = _add_debug_id(debug_labels, debug_coords, - object_id_count, - (dup_coord[1], dup_coord[0])) + object_id_count, + (dup_coord[1], dup_coord[0])) object_id_count += 1 # Combine and colorize components of the debug image debug_img_duplicates_rgb = _draw_ghost_of_duplicates_removed(debug_img_duplicates)
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-1,6 +1,6 @@ ## Interactive Point Annotation Tool -Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it is possible to interactively click to collect coordinates from an image, which can be used in various downstream applications. Left click on the image to collect a point. Right click removes the +Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it is possible to interactively click on an image to collect coordinates, which can be used in various downstream applications. Left click on the image to collect a point. Right click removes the closest collected point. **plantcv.annotate.Points**(*img, figsize=(12,6), label="dafault"*) @@ -13,9 +13,9 @@ closest collected point. - label - The current label (default = "default") - **Attributes:** - - coords - dictionary of all coordinates per group label + - coords - dictionary of all coordinates per sample label - events - includes right and left click events - - count - dictionary that save the counts of different groups (labels) + - count - dictionary that save the counts of different groups (sample_labels) - label - the current label - sample_labels - list of all sample labels, one to one with coordinates collected - view_all - flag indicating whether or not to view all labels @@ -64,14 +64,14 @@ Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it - Remove noise from a microscopy image that is otherwise difficult to filter out with traditional computer vision techniques, and recover stomata that were filtered out during mask cleaning. -**Original Image with "auto-detected" Annotations** - -![Screenshot](img/documentation_images/points_correct_mask/auto_annotated_stomata.png) - **bin_img** ![Screenshot](img/documentation_images/points_correct_mask/bin_mask.png) +**Original Image with "auto-detected" Annotations** + +![Screenshot](img/documentation_images/points_correct_mask/auto_annotated_stomata.png) + ```python import plantcv.plantcv as pcv import plantcv.annotate as pcvan @@ -88,7 +88,7 @@ marker.import_list(coords=centroid_coords, label="stomata") # Filter the binary mask based on corrected annotations corrected_mask = marker.correct_mask(bin_img=bin_mask) -# Optional for visualization +# Optional visualization colorful = pcv.visualize.colorize_label_img(label_img=corrected_mask) # Analysis steps here @@ -97,7 +97,7 @@ size_img = pcv.analyze.size(img=img, labeled_mask=corrected_mask, n_labels=num) **Corrected (and [Colorized](https://plantcv.readthedocs.io/en/stable/visualize_colorize_label_img/)) Mask** -![Screenshot](img/documentation_images/points_correct_mask/colorized_labele_img.png) +![Screenshot](img/documentation_images/points_correct_mask/colorized_label_img.png) **Size Analysis Image** From 1f8d72b04bc4d1290636c9970d2d42529bada42b Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 11:49:47 -0500 Subject: [PATCH 065/162] Delete points_correct_mask.md --- docs/points_correct_mask.md | 60 ------------------------------------- 1 file changed, 60 deletions(-) delete mode 100644 docs/points_correct_mask.md diff --git a/docs/points_correct_mask.md b/docs/points_correct_mask.md deleted file mode 100644 index df72814..0000000 --- a/docs/points_correct_mask.md +++ /dev/null @@ -1,60 +0,0 @@ -## Correct a Mask using Point Annotations - -Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it is possible to interactively click to collect coordinates from an image, then use these coordinate to remove and recover objects from a binary mask. - -**plantcv.annotate.Points.correct_mask**(*bin_img, bin_img_recover*) - -**returns** corrected_mask - -- **Parameters:** - - bin_img - binary image, filtered mask image with selected objects - - bin_img_recover - binary image, unclean mask image with all potentially recoverable objects - -- **Context:** - - Adds objects back to the `bin_mask` if they overlap with an annotation in the [`Points` class instance](Points.md) and can be recovered from the unclean mask `bin_img_recover`. Also checks each object in `bin_mask` and removes - it in the `corrected_mask` if there is not a corresponding annotation. - -- **Example use:** - - Remove noise from a microscopy image that is otherwise difficult to filter out with traditional computer vision - techniques, and recover stomata that were filtered out during mask cleaning. - -**Original Image with Annotations** - -![Screenshot](img/documentation_images/points_correct_mask/annotated_stomata.png) - -**bin_img** - -![Screenshot](img/documentation_images/points_correct_mask/bin_img.png) - -**bin_img_recover** - -![Screenshot](img/documentation_images/points_correct_mask/bin_img_recover.png) - -```python -import plantcv.plantcv as pcv -import plantcv.annotate as pcvan - -# Create an instance of the Points class -img, path, name = pcv.readimage("stomata.tif") - -# Segmentation & mask clean up steps here - -# Create an instance of the Points class & click on stomata -marker = pcvan.Points(img=img, figsize=(12,6)) - -corrected_mask = marker.correct_mask(bin_img=mask_clean, bin_img_recover=bin_img_recover) - -debug_vis = pcv.visualize.overlay_two_imgs(img, corrected_mask, alpha=.4) -``` - -**Corrected Mask** - -![Screenshot](img/documentation_images/points_correct_mask/corrected_mask.png) - -**Overlaid Image** - -![Screenshot](img/documentation_images/points_correct_mask/overlay.png) - - -**Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annotate/classes.py) - From e3ad31d6fe84773fad1edf394049c16872518bdc Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 13:49:01 -0500 Subject: [PATCH 066/162] add "num" objects return --- docs/Points.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/Points.md b/docs/Points.md index 3832364..23a25cd 100644 --- a/docs/Points.md +++ b/docs/Points.md @@ -52,13 +52,13 @@ Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it **plantcv.annotate.Points.correct_mask**(*bin_img*) -**returns** corrected_mask +**returns** corrected_mask, num - **Parameters:** - bin_img - binary image, filtered mask image with selected objects - **Context:** - - Filters objects from the `bin_mask` if they do not overlap with an annotation in the `Points` class instance. Also adds a labeled pixel to the corrected mask if an object cannot be resolved for any annotations. + - Filters objects from the `bin_mask` if they do not overlap with an annotation in the `Points` class instance. Also adds a labeled pixel to the corrected mask if an object cannot be resolved for any annotations. Also returns the number of unique objects in the `corrected_mask` which is useful for downstream analysis. - **Example use:** - Remove noise from a microscopy image that is otherwise difficult to filter out with traditional computer vision @@ -86,7 +86,7 @@ marker = pcvan.Points(img=img, figsize=(12,6)) marker.import_list(coords=centroid_coords, label="stomata") # Filter the binary mask based on corrected annotations -corrected_mask = marker.correct_mask(bin_img=bin_mask) +corrected_mask, num = marker.correct_mask(bin_img=bin_mask) # Optional visualization colorful = pcv.visualize.colorize_label_img(label_img=corrected_mask) From 4a02b57b81c04a69d29c88a73912506d7547ca13 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 13:49:12 -0500 Subject: [PATCH 067/162] add num to function --- plantcv/annotate/classes.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/plantcv/annotate/classes.py b/plantcv/annotate/classes.py index c46b80b..ddcd31e 100644 --- a/plantcv/annotate/classes.py +++ b/plantcv/annotate/classes.py @@ -227,4 +227,7 @@ def correct_mask(self, bin_img): _debug(visual=final_mask, filename=os.path.join(params.debug_outdir, f"{params.device}_annotation-corrected.png")) - return final_mask + # Count the number of objects in the final mask + num = len(np.unique(final_mask)) + + return final_mask, num From 10b9bd467b6504e87e6dd137ff4aad02ed1413de Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 13:49:24 -0500 Subject: [PATCH 068/162] catch the additional return in tests --- tests/test_annotate_points.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py index d2a7a7a..07d8790 100644 --- a/tests/test_annotate_points.py +++ b/tests/test_annotate_points.py @@ -184,7 +184,7 @@ def test_plantcv_annotate_points_correct_mask(test_data): counter = Points(np.copy(allmask), figsize=(8, 6)) counter.import_list(totalpoints1, label="total") - corrected_mask = counter.correct_mask(bin_img=allmask) + corrected_mask, _ = counter.correct_mask(bin_img=allmask) assert np.count_nonzero(corrected_mask) < np.count_nonzero(discs) assert np.count_nonzero(corrected_mask) < np.count_nonzero(allmask) From 17f6b98cb636c28a64202201956444bcccae9bed Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 14:00:01 -0500 Subject: [PATCH 069/162] Update annotated_stomata.png different image replicate before somehow so replace --- .../points_correct_mask/annotated_stomata.png | Bin 133551 -> 138104 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/img/documentation_images/points_correct_mask/annotated_stomata.png b/docs/img/documentation_images/points_correct_mask/annotated_stomata.png index 5957660f6270238090263db5296d9eb00db635de..e6f53776b80ba309ff2d6a40de91fee270c3f899 100644 GIT binary patch literal 138104 zcmeFZcUY6bvoMMRA~gyaIzgl;y=dqGK|s2SbfhIT=|w395D+3YKtw=FC<+SFd+&sZ 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+27,8 @@ closest collected point. - Used to define a list of coordinates of interest. - Can be helpful to ground truth counting algorithms, and exported coordinates could be used in other image analysis workflows. - **Example use:** - - (pcv.roi.multi) - - Shown below (pcv.roi.custom) + - [pcv.roi.multi](https://plantcv.readthedocs.io/en/stable/roi_multi/) + - Shown below [pcv.roi.custom](https://plantcv.readthedocs.io/en/stable/roi_custom/) ```python @@ -64,13 +64,13 @@ Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it - Remove noise from a microscopy image that is otherwise difficult to filter out with traditional computer vision techniques, and recover stomata that were filtered out during mask cleaning. -**Original Image with Annotations** +**Original Image with "auto-detected" Annotations** -![Screenshot](img/documentation_images/points_correct_mask/annotated_stomata.png) +![Screenshot](img/documentation_images/points_correct_mask/auto_annotated_stomata.png) **bin_img** -![Screenshot](img/documentation_images/points_correct_mask/bin_img.png) +![Screenshot](img/documentation_images/points_correct_mask/bin_mask.png) ```python import plantcv.plantcv as pcv @@ -79,22 +79,28 @@ import plantcv.annotate as pcvan # Create an instance of the Points class img, path, name = pcv.readimage("stomata.tif") -# Segmentation & mask clean up steps here +# Segmentation & mask clean up, get_centroids steps here # Create an instance of the Points class & click on stomata marker = pcvan.Points(img=img, figsize=(12,6)) +marker.import_list(coords=centroid_coords, label="stomata") -corrected_mask = marker.correct_mask(bin_img=mask_clean, bin_img_recover=bin_img_recover) +# Filter the binary mask based on corrected annotations +corrected_mask = marker.correct_mask(bin_img=bin_mask) -debug_vis = pcv.visualize.overlay_two_imgs(img, corrected_mask, alpha=.4) +# Optional for visualization +colorful = pcv.visualize.colorize_label_img(label_img=corrected_mask) + +# Analysis steps here +size_img = pcv.analyze.size(img=img, labeled_mask=corrected_mask, n_labels=num) ``` -**Corrected Mask** +**Corrected (and [Colorized](https://plantcv.readthedocs.io/en/stable/visualize_colorize_label_img/)) Mask** -![Screenshot](img/documentation_images/points_correct_mask/corrected_mask.png) +![Screenshot](img/documentation_images/points_correct_mask/colorized_labele_img.png) -**Overlaid Image** +**Size Analysis Image** -![Screenshot](img/documentation_images/points_correct_mask/overlay.png) +![Screenshot](img/documentation_images/points_correct_mask/shape_img.png) **Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annoate/classes.py) From 8e2fe29b35965159fb8210bc7dbb8c877f02fb67 Mon Sep 17 00:00:00 2001 From: HaleySchuhl Date: Thu, 18 Jul 2024 11:27:17 -0500 Subject: [PATCH 063/162] resize doc images and remove the unused old one --- 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