From 087f85f7ace2ec46ed5703d583c9bf3480f083a0 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Tue, 1 Dec 2020 17:34:34 -0600 Subject: [PATCH 01/24] Create display_instances.py --- .../plantcv/visualize/display_instances.py | 196 ++++++++++++++++++ 1 file changed, 196 insertions(+) create mode 100644 plantcv/plantcv/visualize/display_instances.py diff --git a/plantcv/plantcv/visualize/display_instances.py b/plantcv/plantcv/visualize/display_instances.py new file mode 100644 index 000000000..e3a29cb68 --- /dev/null +++ b/plantcv/plantcv/visualize/display_instances.py @@ -0,0 +1,196 @@ +# display instances in an image + +from matplotlib.patches import Polygon +import colorsys +import random +from skimage.measure import find_contours +import matplotlib.pyplot as plt +import numpy as np +from matplotlib import patches, lines +from matplotlib.patches import Polygon +from plantcv.plantcv.visualize import overlay_two_imgs +from plantcv.plantcv.visualize import colorize_masks +from plantcv import plantcv as pcv +from plantcv.plantcv import fatal_error + +def _apply_mask(image, mask, color, alpha=0.5): + """ apply a mask to an input image with a user defined color + :param image: input RGB or grayscale image + :param mask: desired mask + :param color: (a tuple) desired color to show the mask on top of the image + :param alpha: (a value between 0 and 1) transparency value when blending mask and image, by default 0.5 + :return: image with an mask with desired color on top of it + """ + if len(image.shape) == 2: + image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) + for c in range(image.shape[-1]): + image[:, :, c] = np.where(mask == 1, + image[:, :, c] * + (1 - alpha) + alpha * color[c] * 255, + image[:, :, c]) + return image + +def _random_colors(num, bright=True): + """ + Generate desired number of random colors. To get visually distinct colors, generate them in HSV space then convert to RGB. + :param num: number of colors to be generated + :param bright: True or False, if true, the brightness would be 1.0; if False, the brightness would be 0.7. By default it would be True (brightness 0.7) + :return: generated colors (a list of tuples) + """ + + brightness = 1.0 if bright else 0.7 + hsv = [(i / num, 1, brightness) for i in range(num)] + colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) + random.shuffle(colors) + return colors + +def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): + """ + This function is inspired by the same function used in mrcnn, showing different instances with different colors on top of the original image + Users also have the option to specify the color for every instance, as well as the caption for every instance. Showing bounding boxes is another option. + :param image: (required, ndarray) + :param masks: (required, ndarray) + :param figsize: (optional, tuple) the size of the generated figure + :param title: (optional, str) the title of the figure + :param ax: (optional, matplotlib.axes._subplots.AxesSubplot) the axis to plot on. If no axis is passed, create one and automatically call show() + :param colors: (optional, list of tuples, every value should be in the range of [0.0,1.0]) a list of colors to use with each object. If no value is passed, a set of random colors would be used + :param captions: (optional, str) a list of strings to use as captions for each object. If no list of captions is provided, show the local index of the instance + :param show_bbox: (optional, bool) indicator of whether showing the bounding-box + :return:masked_image + :return:colors: colors used to show the instances (same as number of instances) + """ + + if image.shape[0:2] != masks.shape[0:2]: + fatal_error("Sizes of image and mask mismatch!") + # + # auto_show = False + if not ax: + _, ax = plt.subplots(1, figsize=figsize) + # auto_show = True + + num_insts = masks.shape[2] + # Generate random colors + colors = colors or _random_colors(num_insts) + if len(colors) < num_insts: + fatal_error("Not enough colors provided to show all instances!") + if len(colors) > num_insts: + colors = colors[0:num_insts] + + # Show area outside image boundaries. + height, width = image.shape[:2] + ax.set_ylim(height + 10, -10) + ax.set_xlim(-10, width + 10) + ax.axis('off') + ax.set_title(title) + + masks_ = [masks[:, :, i] for i in range(num_insts)] + colors_ = [tuple([x * 255 for x in color]) for color in colors] + colorized_mask = pcv.visualize.colorize_masks(masks_, colors_) + masked_image = pcv.visualize.overlay_two_imgs(image, colorized_mask, alpha=0.5) + + # masked_image = image.astype(np.uint32).copy() + for i in range(num_insts): + color = colors[i] + + # Mask + mask = masks[:, :, i] + # masked_image = _apply_mask(masked_image, mask, color) + + ys, xs = np.where(mask > 0) + x1, x2 = min(xs), max(xs) + y1, y2 = min(ys), max(ys) + if show_bbox: + p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2, alpha=0.7, linestyle="dashed", + edgecolor=color, facecolor='none') + ax.add_patch(p) + + # Mask Polygon + # Pad to ensure proper polygons for masks that touch image edges. + padded_mask = np.zeros( + (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8) + padded_mask[1:-1, 1:-1] = mask + contours = find_contours(padded_mask, 0.5) + for verts in contours: + # Subtract the padding and flip (y, x) to (x, y) + verts = np.fliplr(verts) - 1 + p = Polygon(verts, facecolor="none", edgecolor=color) + ax.add_patch(p) + if not captions: + caption = str(i) + else: + caption = captions[i] + ax.text(x1, y1 + 8, caption, + color='w', size=13, backgroundcolor="none") + ax.imshow(masked_image.astype(np.uint8)) + return masked_image, colors + +# former definition of this function, relies on the definition of the local funciton "_apply_mask" +def display_instances_archived(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): + """ + This function is inspired by the function in mrcnn + masks: [height, width, num_instances] + figsize: (optional) the size of the image + title: (optional) Figure title + ax (optional): the axis to plot on. If no axis is passed, create one and automatically call show() + colors: (optional) An array or colors to use with each object + captions: (optional) A list of strings to use as captions for each object. If no list of captions is provided, show the index of the instance + show_bbox: (optional) + """ + if image.shape[0:2] != masks.shape[0:2]: + fatal_error("Sizes of image and mask mismatch!") + # + # auto_show = False + if not ax: + _, ax = plt.subplots(1, figsize=figsize) + # auto_show = True + + num_insts = masks.shape[2] + # Generate random colors + colors = colors or _random_colors(num_insts) + if len(colors) < num_insts: + fatal_error("Not enough colors provided to show all instances!") + if len(colors) > num_insts: + colors = colors[0:num_insts] + + # Show area outside image boundaries. + height, width = image.shape[:2] + ax.set_ylim(height + 10, -10) + ax.set_xlim(-10, width + 10) + ax.axis('off') + ax.set_title(title) + + masked_image = image.astype(np.uint32).copy() + for i in range(num_insts): + color = colors[i] + + # Mask + mask = masks[:, :, i] + masked_image = _apply_mask(masked_image, mask, color) + + ys, xs = np.where(mask > 0) + x1, x2 = min(xs), max(xs) + y1, y2 = min(ys), max(ys) + if show_bbox: + p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2, alpha=0.7, linestyle="dashed", + edgecolor=color, facecolor='none') + ax.add_patch(p) + + # Mask Polygon + # Pad to ensure proper polygons for masks that touch image edges. + padded_mask = np.zeros( + (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8) + padded_mask[1:-1, 1:-1] = mask + contours = find_contours(padded_mask, 0.5) + for verts in contours: + # Subtract the padding and flip (y, x) to (x, y) + verts = np.fliplr(verts) - 1 + p = Polygon(verts, facecolor="none", edgecolor=color) + ax.add_patch(p) + if not captions: + caption = str(i) + else: + caption = captions[i] + ax.text(x1, y1 + 8, caption, + color='w', size=13, backgroundcolor="none") + ax.imshow(masked_image.astype(np.uint8)) + return masked_image, colors From 1ea34c475405458e5cdd73c7fb899287f85e8a59 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Tue, 1 Dec 2020 17:34:40 -0600 Subject: [PATCH 02/24] Update __init__.py --- plantcv/plantcv/visualize/__init__.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/plantcv/plantcv/visualize/__init__.py b/plantcv/plantcv/visualize/__init__.py index 77b8cbddb..e0f0e2b1a 100644 --- a/plantcv/plantcv/visualize/__init__.py +++ b/plantcv/plantcv/visualize/__init__.py @@ -5,6 +5,7 @@ from plantcv.plantcv.visualize.colorspaces import colorspaces from plantcv.plantcv.visualize.auto_threshold_methods import auto_threshold_methods from plantcv.plantcv.visualize.overlay_two_imgs import overlay_two_imgs +from plantcv.plantcv.visualize.display_instances import display_instances __all__ = ["pseudocolor", "colorize_masks", "histogram", "clustered_contours", "colorspaces", "auto_threshold_methods", - "overlay_two_imgs"] + "overlay_two_imgs","display_instances"] From 25e413e8c5a288446a70fa0c6e35e4a491060c66 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Tue, 1 Dec 2020 17:34:51 -0600 Subject: [PATCH 03/24] upload test data --- 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z009C72oNAZfB*pk1PBlyK!5-N0t5&UAV7cs0RjXF5FkK+009C72oNAZfB*pk1PBly zK!5-N0t5&UAV7cs0RjXF5FkK+009C72oNAZfB*pk1PBlyK!5-N0t5&UAV7cs0RjXF z5FkK+009C72oNAZfB*pk1PBlyK!5-N0t5&UAV7cs0RjXF5FkK+009C72oNAZfB*pk z1PBlyK!5-N0t5&UAV7cs0Rm+UtUvc~{rOuro@%)*Wdfjb{OKKkMMx9&Xi z-ukz%ufOo@@#^@Q;E>d|K5BbHSd4cyxeJCpKQMW zsrmj$^ZlofuTP%;a`XLP%{?D$UT-$vC+pv8Uf*cGpK88;*nEG!`F_6n{%rGovd2kX z>t`RXfA`jnUuZ5LyngTg?FZ}MJ8SXxPg;EL`ud9}EjCU5X#M=158rsAx$~PZum9lq z=y>(s`i1N37oR Date: Tue, 1 Dec 2020 17:34:55 -0600 Subject: [PATCH 04/24] Update tests.py --- tests/tests.py | 32 +++++++++++++++++++++++++++++++- 1 file changed, 31 insertions(+), 1 deletion(-) diff --git a/tests/tests.py b/tests/tests.py index a578ec018..aa558a4fa 100755 --- a/tests/tests.py +++ b/tests/tests.py @@ -18,6 +18,7 @@ import matplotlib import dask from dask.distributed import Client +import pickle as pkl PARALLEL_TEST_DATA = os.path.join(os.path.dirname(os.path.abspath(__file__)), "parallel_data") TEST_TMPDIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", ".cache") @@ -942,7 +943,8 @@ def test_plantcv_parallel_process_results_invalid_json(): TEST_THERMAL_IMG_MASK = "thermal_img_mask.png" TEST_INPUT_THERMAL_CSV = "FLIR2600.csv" PIXEL_VALUES = "pixel_inspector_rgb_values.txt" - +TEST_INPUT_INSTANCE_IMG = "visualize_inst_seg_img.png" +TEST_INPUT_INSTANCE_MASK = "visualize_inst_seg_mask.pkl" # ########################## # Tests for the main package @@ -6074,6 +6076,34 @@ def test_plantcv_visualize_overlay_two_imgs_size_mismatch(): with pytest.raises(RuntimeError): _ = pcv.visualize.overlay_two_imgs(img1=img1, img2=img2) +def test_plantcv_visualize_display_instances(tmpdir): + + img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") + masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] + _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, + show_bbox=True) + assert len(colors) == masks.shape[2] + +def test_plantcv_visualize_display_instances_bad_color(tmpdir): + import colorsys + import random + img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") + masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] + num = 2 + hsv = [(i / num, 1, 1.0) for i in range(num)] + colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) + random.shuffle(colors) + with pytest.raises(RuntimeError): + _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, + show_bbox=True) + +def test_plantcv_visualize_display_instances_bad_size(tmpdir): + img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") + img = img[0:100,0:100,:] + masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] + with pytest.raises(RuntimeError): + _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, + show_bbox=True) # ############################## # Tests for the utils subpackage From fe3f21e666f4d76777b09a28aaa133e14c6d4c22 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Tue, 1 Dec 2020 17:46:56 -0600 Subject: [PATCH 05/24] Update display_instances.py --- plantcv/plantcv/visualize/display_instances.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/plantcv/plantcv/visualize/display_instances.py b/plantcv/plantcv/visualize/display_instances.py index e3a29cb68..11fe8e214 100644 --- a/plantcv/plantcv/visualize/display_instances.py +++ b/plantcv/plantcv/visualize/display_instances.py @@ -1,5 +1,5 @@ # display instances in an image - +import cv2 from matplotlib.patches import Polygon import colorsys import random From d96adac1aaebd776e57c5cd5004149893702db55 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Tue, 1 Dec 2020 20:48:27 -0600 Subject: [PATCH 06/24] Update display_instances.py --- .../plantcv/visualize/display_instances.py | 172 +++++++++--------- 1 file changed, 86 insertions(+), 86 deletions(-) diff --git a/plantcv/plantcv/visualize/display_instances.py b/plantcv/plantcv/visualize/display_instances.py index 11fe8e214..cbf22cc9c 100644 --- a/plantcv/plantcv/visualize/display_instances.py +++ b/plantcv/plantcv/visualize/display_instances.py @@ -13,22 +13,22 @@ from plantcv import plantcv as pcv from plantcv.plantcv import fatal_error -def _apply_mask(image, mask, color, alpha=0.5): - """ apply a mask to an input image with a user defined color - :param image: input RGB or grayscale image - :param mask: desired mask - :param color: (a tuple) desired color to show the mask on top of the image - :param alpha: (a value between 0 and 1) transparency value when blending mask and image, by default 0.5 - :return: image with an mask with desired color on top of it - """ - if len(image.shape) == 2: - image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) - for c in range(image.shape[-1]): - image[:, :, c] = np.where(mask == 1, - image[:, :, c] * - (1 - alpha) + alpha * color[c] * 255, - image[:, :, c]) - return image +# def _apply_mask(image, mask, color, alpha=0.5): +# """ apply a mask to an input image with a user defined color +# :param image: input RGB or grayscale image +# :param mask: desired mask +# :param color: (a tuple) desired color to show the mask on top of the image +# :param alpha: (a value between 0 and 1) transparency value when blending mask and image, by default 0.5 +# :return: image with an mask with desired color on top of it +# """ +# if len(image.shape) == 2: +# image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) +# for c in range(image.shape[-1]): +# image[:, :, c] = np.where(mask == 1, +# image[:, :, c] * +# (1 - alpha) + alpha * color[c] * 255, +# image[:, :, c]) +# return image def _random_colors(num, bright=True): """ @@ -124,73 +124,73 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= ax.imshow(masked_image.astype(np.uint8)) return masked_image, colors -# former definition of this function, relies on the definition of the local funciton "_apply_mask" -def display_instances_archived(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): - """ - This function is inspired by the function in mrcnn - masks: [height, width, num_instances] - figsize: (optional) the size of the image - title: (optional) Figure title - ax (optional): the axis to plot on. If no axis is passed, create one and automatically call show() - colors: (optional) An array or colors to use with each object - captions: (optional) A list of strings to use as captions for each object. If no list of captions is provided, show the index of the instance - show_bbox: (optional) - """ - if image.shape[0:2] != masks.shape[0:2]: - fatal_error("Sizes of image and mask mismatch!") - # - # auto_show = False - if not ax: - _, ax = plt.subplots(1, figsize=figsize) - # auto_show = True - - num_insts = masks.shape[2] - # Generate random colors - colors = colors or _random_colors(num_insts) - if len(colors) < num_insts: - fatal_error("Not enough colors provided to show all instances!") - if len(colors) > num_insts: - colors = colors[0:num_insts] - - # Show area outside image boundaries. - height, width = image.shape[:2] - ax.set_ylim(height + 10, -10) - ax.set_xlim(-10, width + 10) - ax.axis('off') - ax.set_title(title) - - masked_image = image.astype(np.uint32).copy() - for i in range(num_insts): - color = colors[i] - - # Mask - mask = masks[:, :, i] - masked_image = _apply_mask(masked_image, mask, color) - - ys, xs = np.where(mask > 0) - x1, x2 = min(xs), max(xs) - y1, y2 = min(ys), max(ys) - if show_bbox: - p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2, alpha=0.7, linestyle="dashed", - edgecolor=color, facecolor='none') - ax.add_patch(p) - - # Mask Polygon - # Pad to ensure proper polygons for masks that touch image edges. - padded_mask = np.zeros( - (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8) - padded_mask[1:-1, 1:-1] = mask - contours = find_contours(padded_mask, 0.5) - for verts in contours: - # Subtract the padding and flip (y, x) to (x, y) - verts = np.fliplr(verts) - 1 - p = Polygon(verts, facecolor="none", edgecolor=color) - ax.add_patch(p) - if not captions: - caption = str(i) - else: - caption = captions[i] - ax.text(x1, y1 + 8, caption, - color='w', size=13, backgroundcolor="none") - ax.imshow(masked_image.astype(np.uint8)) - return masked_image, colors +# # former definition of this function, relies on the definition of the local funciton "_apply_mask" +# def display_instances_archived(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): +# """ +# This function is inspired by the function in mrcnn +# masks: [height, width, num_instances] +# figsize: (optional) the size of the image +# title: (optional) Figure title +# ax (optional): the axis to plot on. If no axis is passed, create one and automatically call show() +# colors: (optional) An array or colors to use with each object +# captions: (optional) A list of strings to use as captions for each object. If no list of captions is provided, show the index of the instance +# show_bbox: (optional) +# """ +# if image.shape[0:2] != masks.shape[0:2]: +# fatal_error("Sizes of image and mask mismatch!") +# # +# # auto_show = False +# if not ax: +# _, ax = plt.subplots(1, figsize=figsize) +# # auto_show = True +# +# num_insts = masks.shape[2] +# # Generate random colors +# colors = colors or _random_colors(num_insts) +# if len(colors) < num_insts: +# fatal_error("Not enough colors provided to show all instances!") +# if len(colors) > num_insts: +# colors = colors[0:num_insts] +# +# # Show area outside image boundaries. +# height, width = image.shape[:2] +# ax.set_ylim(height + 10, -10) +# ax.set_xlim(-10, width + 10) +# ax.axis('off') +# ax.set_title(title) +# +# masked_image = image.astype(np.uint32).copy() +# for i in range(num_insts): +# color = colors[i] +# +# # Mask +# mask = masks[:, :, i] +# masked_image = _apply_mask(masked_image, mask, color) +# +# ys, xs = np.where(mask > 0) +# x1, x2 = min(xs), max(xs) +# y1, y2 = min(ys), max(ys) +# if show_bbox: +# p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2, alpha=0.7, linestyle="dashed", +# edgecolor=color, facecolor='none') +# ax.add_patch(p) +# +# # Mask Polygon +# # Pad to ensure proper polygons for masks that touch image edges. +# padded_mask = np.zeros( +# (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8) +# padded_mask[1:-1, 1:-1] = mask +# contours = find_contours(padded_mask, 0.5) +# for verts in contours: +# # Subtract the padding and flip (y, x) to (x, y) +# verts = np.fliplr(verts) - 1 +# p = Polygon(verts, facecolor="none", edgecolor=color) +# ax.add_patch(p) +# if not captions: +# caption = str(i) +# else: +# caption = captions[i] +# ax.text(x1, y1 + 8, caption, +# color='w', size=13, backgroundcolor="none") +# ax.imshow(masked_image.astype(np.uint8)) +# return masked_image, colors From c3fcc18495d6108eb091c36eac8a6a829a392e86 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Tue, 1 Dec 2020 20:48:29 -0600 Subject: [PATCH 07/24] Update tests.py --- tests/tests.py | 25 +++++++++++++++++++++++++ 1 file changed, 25 insertions(+) diff --git a/tests/tests.py b/tests/tests.py index aa558a4fa..4f0c81093 100755 --- a/tests/tests.py +++ b/tests/tests.py @@ -6084,6 +6084,16 @@ def test_plantcv_visualize_display_instances(tmpdir): show_bbox=True) assert len(colors) == masks.shape[2] +def test_plantcv_visualize_display_instances_captions(tmpdir): + + img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") + masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] + captions = [str(i) for i in range(masks.shape[2])] + _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=captions, + show_bbox=True) + assert len(colors) == masks.shape[2] + + def test_plantcv_visualize_display_instances_bad_color(tmpdir): import colorsys import random @@ -6097,6 +6107,19 @@ def test_plantcv_visualize_display_instances_bad_color(tmpdir): _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, show_bbox=True) +def test_plantcv_visualize_display_instances_bad_color2(tmpdir): + import colorsys + import random + img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") + masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] + num = 20 + hsv = [(i / num, 1, 1.0) for i in range(num)] + colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) + random.shuffle(colors) + _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, + show_bbox=True) + assert len(colors) == masks.shape[2] + def test_plantcv_visualize_display_instances_bad_size(tmpdir): img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") img = img[0:100,0:100,:] @@ -6105,6 +6128,8 @@ def test_plantcv_visualize_display_instances_bad_size(tmpdir): _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True) + + # ############################## # Tests for the utils subpackage # ############################## From 6a599dd708c79218648bb7ce0c45aac0237d6889 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 2 Dec 2020 15:03:27 -0600 Subject: [PATCH 08/24] Create visualize_display_instances.md --- docs/visualize_display_instances.md | 65 +++++++++++++++++++++++++++++ 1 file changed, 65 insertions(+) create mode 100644 docs/visualize_display_instances.md diff --git a/docs/visualize_display_instances.md b/docs/visualize_display_instances.md new file mode 100644 index 000000000..548e65944 --- /dev/null +++ b/docs/visualize_display_instances.md @@ -0,0 +1,65 @@ +## Display Instances + +This function displays different object intances in different colors on top of the original image. + +**plantcv.visualize.display_instances**(*img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True*) +**returns** masked_img, colors + +- **Parameters:** + - img - (required, ndarray)input image + - masks - (required, ndarray) instance masks represented by a 3-d array, the 3rd dimension represents the number of insatnces to show. + - figsize - (optional, tuple) the size of the generated figure + - title - (optional, str) the title of the figure + - ax - (optional, matplotlib.axes._subplots.AxesSubplot) the axis to plot on. If no axis is passed, create one and automatically call show()) + - colors - (optional, list of tuples, every value should be in the range of [0.0,1.0]) a list of colors to use with each object. If no value is passed, a set of random colors would be used + - captions - (optional, str) a list of strings to use as captions for each object. If no list of captions is provided, show the local index of the instance + - show_bbox - (optional, bool) indicator of whether showing the bounding-box + +- **Context:** + - Used to display different segmented instances on top of the original image. +- **Example use:** + - Below + +**Original image: RGB image** + +![Screenshot](img/documentation_images/visualize_display_instances/visualize_inst_seg_img.png) + +**masks: 10 different segmentation masks represent for different leaves** + +![Screenshot](img/documentation_images/visualize_display_instances/mask_0.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_1.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_2.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_3.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_4.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_5.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_6.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_7.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_8.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_9.png) +![Screenshot](img/documentation_images/visualize_display_instances/mask_10.png) + + +```python + +from plantcv import plantcv as pcv + +masked_img,colors = pcv.visualize.display_instances(img, masks, figsize=(10, 10), title="", ax=None, colors=None, captions=None, show_bbox=True) + +# option to add customized captions and/or customized figure title and/or not showing the bounding box +captions = ["leaf{}".format(i) for i in range(masks.shape[2])] +_,_ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="Visualization of segmentation", ax=None, colors=None, captions=captions, show_bbox=False) + +# the number of instances to display depends on the number of input masks +# the colors can also be customized +masks_reduced = masks[:,:,2:7], +colors = [(0.0,1.0,0.2),(0.4,0.0,1.0),(0.5,1.0,0.0),(1.0,0.6,0.0),(0.9,0.0,1.0)] +_,_= pcv.visualize.display_instances(img, masks_reduced, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, show_bbox=True) + +``` + +**Blended Image** + +![Screenshot](img/documentation_images/visualize_display_instances/result1.png) +![Screenshot](img/documentation_images/visualize_display_instances/result2.png) +![Screenshot](img/documentation_images/visualize_display_instances/result3.png) +**Source Code:** [Here](https://github.com/danforthcenter/plantcv/blob/master/plantcv/plantcv/visualize/display_instances.py) From 6eae9af5b1d592a290026f36ca864f11a547f1e7 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 2 Dec 2020 15:03:39 -0600 Subject: [PATCH 09/24] upload documentation images --- .../visualize_display_instances/mask_0.png | Bin 0 -> 5878 bytes .../visualize_display_instances/mask_1.png | Bin 0 -> 5706 bytes .../visualize_display_instances/mask_10.png | Bin 0 -> 4134 bytes .../visualize_display_instances/mask_2.png | Bin 0 -> 5102 bytes .../visualize_display_instances/mask_3.png | Bin 0 -> 6042 bytes .../visualize_display_instances/mask_4.png | Bin 0 -> 5332 bytes .../visualize_display_instances/mask_5.png | Bin 0 -> 5275 bytes .../visualize_display_instances/mask_6.png | Bin 0 -> 4705 bytes .../visualize_display_instances/mask_7.png | Bin 0 -> 4456 bytes .../visualize_display_instances/mask_8.png | Bin 0 -> 4663 bytes .../visualize_display_instances/mask_9.png | Bin 0 -> 4698 bytes .../visualize_display_instances/result1.png | Bin 0 -> 74832 bytes .../visualize_display_instances/result2.png | Bin 0 -> 301759 bytes .../visualize_display_instances/result3.png | Bin 0 -> 287193 bytes .../visualize_inst_seg_img.png | Bin 0 -> 127874 bytes 15 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 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z;tZl4#~yvs3};OXKi=vY_t%{Hwp1}m2d~93TPt68nC%Fvkw-K~;heWOeZi=@*!%vL zj_`uiC@Rn%0wF}VrX*g}r1KeX$q9QN5P~ZY-b8JNl5EQ|Ei6&6#7~2Y*3! z!`r_D$M8YywybN?m>bBWNX%wy@)wT?iTm{#i5reDH_MDC54cbND!=I{q7wzm(t)le zLSDQZ@nuH+U!%T=Jzvj$5&P^V`#&~DzIfhYwz>bea#5%xks@T_?B{dC{}eGL=%M{@ zyZUFpvl!zO?bqjl`A-pglFfhX$o?dKmRN5z68t~<6rV5ro$>x#2QVv5hn+`i>!to* zUC+WR{?n)bh=x7uoehEzDF3&cil{?;{~7aV(dszQdSO*NQva)2iLM#*e??oEePj|f>hY$n8irz%ns@~qdoI|b|i8XCAw`Tvdj|1Ia literal 0 HcmV?d00001 From 8783ed16f0effbdcfcee21531d3787cbdf187a14 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Thu, 11 Feb 2021 11:02:41 -0600 Subject: [PATCH 10/24] Update display_instances.py --- .../plantcv/visualize/display_instances.py | 200 +++++++++--------- 1 file changed, 102 insertions(+), 98 deletions(-) diff --git a/plantcv/plantcv/visualize/display_instances.py b/plantcv/plantcv/visualize/display_instances.py index cbf22cc9c..76deceb1b 100644 --- a/plantcv/plantcv/visualize/display_instances.py +++ b/plantcv/plantcv/visualize/display_instances.py @@ -8,27 +8,27 @@ import numpy as np from matplotlib import patches, lines from matplotlib.patches import Polygon -from plantcv.plantcv.visualize import overlay_two_imgs -from plantcv.plantcv.visualize import colorize_masks +# from plantcv.plantcv.visualize import overlay_two_imgs +# from plantcv.plantcv.visualize import colorize_masks from plantcv import plantcv as pcv from plantcv.plantcv import fatal_error -# def _apply_mask(image, mask, color, alpha=0.5): -# """ apply a mask to an input image with a user defined color -# :param image: input RGB or grayscale image -# :param mask: desired mask -# :param color: (a tuple) desired color to show the mask on top of the image -# :param alpha: (a value between 0 and 1) transparency value when blending mask and image, by default 0.5 -# :return: image with an mask with desired color on top of it -# """ -# if len(image.shape) == 2: -# image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) -# for c in range(image.shape[-1]): -# image[:, :, c] = np.where(mask == 1, -# image[:, :, c] * -# (1 - alpha) + alpha * color[c] * 255, -# image[:, :, c]) -# return image +def _overlay_mask_on_image(image, mask, color, alpha=0.5): + """ apply a mask to an input image with a user defined color + :param image: input RGB or grayscale image + :param mask: desired mask + :param color: (a tuple) desired color to show the mask on top of the image + :param alpha: (a value between 0 and 1) transparency value when blending mask and image, by default 0.5 + :return: image with an mask with desired color on top of it + """ + if len(image.shape) == 2: + image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) + for c in range(image.shape[-1]): + image[:, :, c] = np.where(mask == 1, + image[:, :, c] * + (1 - alpha) + alpha * color[c] * 255, + image[:, :, c]) + return image def _random_colors(num, bright=True): """ @@ -44,6 +44,87 @@ def _random_colors(num, bright=True): random.shuffle(colors) return colors +# def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): +# """ +# This function is inspired by the same function used in mrcnn, showing different instances with different colors on top of the original image +# Users also have the option to specify the color for every instance, as well as the caption for every instance. Showing bounding boxes is another option. +# :param image: (required, ndarray) +# :param masks: (required, ndarray) +# :param figsize: (optional, tuple) the size of the generated figure +# :param title: (optional, str) the title of the figure +# :param ax: (optional, matplotlib.axes._subplots.AxesSubplot) the axis to plot on. If no axis is passed, create one and automatically call show() +# :param colors: (optional, list of tuples, every value should be in the range of [0.0,1.0]) a list of colors to use with each object. If no value is passed, a set of random colors would be used +# :param captions: (optional, str) a list of strings to use as captions for each object. If no list of captions is provided, show the local index of the instance +# :param show_bbox: (optional, bool) indicator of whether showing the bounding-box +# :return:masked_image +# :return:colors: colors used to show the instances (same as number of instances) +# """ +# +# if image.shape[0:2] != masks.shape[0:2]: +# fatal_error("Sizes of image and mask mismatch!") +# # +# # auto_show = False +# if not ax: +# _, ax = plt.subplots(1, figsize=figsize) +# # auto_show = True +# +# num_insts = masks.shape[2] +# # Generate random colors +# colors = colors or _random_colors(num_insts) +# if len(colors) < num_insts: +# fatal_error("Not enough colors provided to show all instances!") +# if len(colors) > num_insts: +# colors = colors[0:num_insts] +# +# # Show area outside image boundaries. +# height, width = image.shape[:2] +# ax.set_ylim(height + 10, -10) +# ax.set_xlim(-10, width + 10) +# ax.axis('off') +# ax.set_title(title) +# +# masks_ = [masks[:, :, i] for i in range(num_insts)] +# colors_ = [tuple([x * 255 for x in color]) for color in colors] +# colorized_mask = pcv.visualize.colorize_masks(masks_, colors_) +# masked_image = pcv.visualize.overlay_two_imgs(image, colorized_mask, alpha=0.5) +# +# # masked_image = image.astype(np.uint32).copy() +# for i in range(num_insts): +# color = colors[i] +# +# # Mask +# mask = masks[:, :, i] +# # masked_image = _apply_mask(masked_image, mask, color) +# +# ys, xs = np.where(mask > 0) +# x1, x2 = min(xs), max(xs) +# y1, y2 = min(ys), max(ys) +# if show_bbox: +# p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2, alpha=0.7, linestyle="dashed", +# edgecolor=color, facecolor='none') +# ax.add_patch(p) +# +# # Mask Polygon +# # Pad to ensure proper polygons for masks that touch image edges. +# padded_mask = np.zeros( +# (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8) +# padded_mask[1:-1, 1:-1] = mask +# contours = find_contours(padded_mask, 0.5) +# for verts in contours: +# # Subtract the padding and flip (y, x) to (x, y) +# verts = np.fliplr(verts) - 1 +# p = Polygon(verts, facecolor="none", edgecolor=color) +# ax.add_patch(p) +# if not captions: +# caption = str(i) +# else: +# caption = captions[i] +# ax.text(x1, y1 + 8, caption, +# color='w', size=13, backgroundcolor="none") +# ax.imshow(masked_image.astype(np.uint8)) +# return masked_image, colors + +# former definition of this function, relies on the definition of the local funciton "_apply_mask" def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): """ This function is inspired by the same function used in mrcnn, showing different instances with different colors on top of the original image @@ -59,7 +140,6 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= :return:masked_image :return:colors: colors used to show the instances (same as number of instances) """ - if image.shape[0:2] != masks.shape[0:2]: fatal_error("Sizes of image and mask mismatch!") # @@ -76,25 +156,20 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= if len(colors) > num_insts: colors = colors[0:num_insts] - # Show area outside image boundaries. + # Show area outside image boundaries. height, width = image.shape[:2] ax.set_ylim(height + 10, -10) ax.set_xlim(-10, width + 10) ax.axis('off') ax.set_title(title) - masks_ = [masks[:, :, i] for i in range(num_insts)] - colors_ = [tuple([x * 255 for x in color]) for color in colors] - colorized_mask = pcv.visualize.colorize_masks(masks_, colors_) - masked_image = pcv.visualize.overlay_two_imgs(image, colorized_mask, alpha=0.5) - - # masked_image = image.astype(np.uint32).copy() + masked_image = image.astype(np.uint32).copy() for i in range(num_insts): color = colors[i] # Mask mask = masks[:, :, i] - # masked_image = _apply_mask(masked_image, mask, color) + masked_image = _overlay_mask_on_image(masked_image, mask, color) ys, xs = np.where(mask > 0) x1, x2 = min(xs), max(xs) @@ -123,74 +198,3 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= color='w', size=13, backgroundcolor="none") ax.imshow(masked_image.astype(np.uint8)) return masked_image, colors - -# # former definition of this function, relies on the definition of the local funciton "_apply_mask" -# def display_instances_archived(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): -# """ -# This function is inspired by the function in mrcnn -# masks: [height, width, num_instances] -# figsize: (optional) the size of the image -# title: (optional) Figure title -# ax (optional): the axis to plot on. If no axis is passed, create one and automatically call show() -# colors: (optional) An array or colors to use with each object -# captions: (optional) A list of strings to use as captions for each object. If no list of captions is provided, show the index of the instance -# show_bbox: (optional) -# """ -# if image.shape[0:2] != masks.shape[0:2]: -# fatal_error("Sizes of image and mask mismatch!") -# # -# # auto_show = False -# if not ax: -# _, ax = plt.subplots(1, figsize=figsize) -# # auto_show = True -# -# num_insts = masks.shape[2] -# # Generate random colors -# colors = colors or _random_colors(num_insts) -# if len(colors) < num_insts: -# fatal_error("Not enough colors provided to show all instances!") -# if len(colors) > num_insts: -# colors = colors[0:num_insts] -# -# # Show area outside image boundaries. -# height, width = image.shape[:2] -# ax.set_ylim(height + 10, -10) -# ax.set_xlim(-10, width + 10) -# ax.axis('off') -# ax.set_title(title) -# -# masked_image = image.astype(np.uint32).copy() -# for i in range(num_insts): -# color = colors[i] -# -# # Mask -# mask = masks[:, :, i] -# masked_image = _apply_mask(masked_image, mask, color) -# -# ys, xs = np.where(mask > 0) -# x1, x2 = min(xs), max(xs) -# y1, y2 = min(ys), max(ys) -# if show_bbox: -# p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2, alpha=0.7, linestyle="dashed", -# edgecolor=color, facecolor='none') -# ax.add_patch(p) -# -# # Mask Polygon -# # Pad to ensure proper polygons for masks that touch image edges. -# padded_mask = np.zeros( -# (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8) -# padded_mask[1:-1, 1:-1] = mask -# contours = find_contours(padded_mask, 0.5) -# for verts in contours: -# # Subtract the padding and flip (y, x) to (x, y) -# verts = np.fliplr(verts) - 1 -# p = Polygon(verts, facecolor="none", edgecolor=color) -# ax.add_patch(p) -# if not captions: -# caption = str(i) -# else: -# caption = captions[i] -# ax.text(x1, y1 + 8, caption, -# color='w', size=13, backgroundcolor="none") -# ax.imshow(masked_image.astype(np.uint8)) -# return masked_image, colors From 9ce5f6dd4d261989f37e3bc9e50a9158f3b4b91a Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Thu, 18 Mar 2021 18:48:58 -0500 Subject: [PATCH 11/24] Update display_instances.py --- .../plantcv/visualize/display_instances.py | 148 ++++++------------ 1 file changed, 45 insertions(+), 103 deletions(-) diff --git a/plantcv/plantcv/visualize/display_instances.py b/plantcv/plantcv/visualize/display_instances.py index 76deceb1b..881fd63cf 100644 --- a/plantcv/plantcv/visualize/display_instances.py +++ b/plantcv/plantcv/visualize/display_instances.py @@ -8,10 +8,12 @@ import numpy as np from matplotlib import patches, lines from matplotlib.patches import Polygon -# from plantcv.plantcv.visualize import overlay_two_imgs -# from plantcv.plantcv.visualize import colorize_masks from plantcv import plantcv as pcv from plantcv.plantcv import fatal_error +from plantcv.plantcv import params +from plantcv.plantcv import plot_image +from plantcv.plantcv import print_image +import os def _overlay_mask_on_image(image, mask, color, alpha=0.5): """ apply a mask to an input image with a user defined color @@ -22,7 +24,7 @@ def _overlay_mask_on_image(image, mask, color, alpha=0.5): :return: image with an mask with desired color on top of it """ if len(image.shape) == 2: - image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) + image = cv2.cvtColor(image.astype(np.uint8), cv2.COLOR_GRAY2BGR) for c in range(image.shape[-1]): image[:, :, c] = np.where(mask == 1, image[:, :, c] * @@ -30,101 +32,20 @@ def _overlay_mask_on_image(image, mask, color, alpha=0.5): image[:, :, c]) return image -def _random_colors(num, bright=True): - """ - Generate desired number of random colors. To get visually distinct colors, generate them in HSV space then convert to RGB. - :param num: number of colors to be generated - :param bright: True or False, if true, the brightness would be 1.0; if False, the brightness would be 0.7. By default it would be True (brightness 0.7) - :return: generated colors (a list of tuples) - """ - - brightness = 1.0 if bright else 0.7 - hsv = [(i / num, 1, brightness) for i in range(num)] - colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) - random.shuffle(colors) - return colors - -# def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): +# def _random_colors(num, bright=True): # """ -# This function is inspired by the same function used in mrcnn, showing different instances with different colors on top of the original image -# Users also have the option to specify the color for every instance, as well as the caption for every instance. Showing bounding boxes is another option. -# :param image: (required, ndarray) -# :param masks: (required, ndarray) -# :param figsize: (optional, tuple) the size of the generated figure -# :param title: (optional, str) the title of the figure -# :param ax: (optional, matplotlib.axes._subplots.AxesSubplot) the axis to plot on. If no axis is passed, create one and automatically call show() -# :param colors: (optional, list of tuples, every value should be in the range of [0.0,1.0]) a list of colors to use with each object. If no value is passed, a set of random colors would be used -# :param captions: (optional, str) a list of strings to use as captions for each object. If no list of captions is provided, show the local index of the instance -# :param show_bbox: (optional, bool) indicator of whether showing the bounding-box -# :return:masked_image -# :return:colors: colors used to show the instances (same as number of instances) +# Generate desired number of random colors. To get visually distinct colors, generate them in HSV space then convert to RGB. +# :param num: number of colors to be generated +# :param bright: True or False, if true, the brightness would be 1.0; if False, the brightness would be 0.7. By default it would be True (brightness 0.7) +# :return: generated colors (a list of tuples) # """ # -# if image.shape[0:2] != masks.shape[0:2]: -# fatal_error("Sizes of image and mask mismatch!") -# # -# # auto_show = False -# if not ax: -# _, ax = plt.subplots(1, figsize=figsize) -# # auto_show = True -# -# num_insts = masks.shape[2] -# # Generate random colors -# colors = colors or _random_colors(num_insts) -# if len(colors) < num_insts: -# fatal_error("Not enough colors provided to show all instances!") -# if len(colors) > num_insts: -# colors = colors[0:num_insts] -# -# # Show area outside image boundaries. -# height, width = image.shape[:2] -# ax.set_ylim(height + 10, -10) -# ax.set_xlim(-10, width + 10) -# ax.axis('off') -# ax.set_title(title) -# -# masks_ = [masks[:, :, i] for i in range(num_insts)] -# colors_ = [tuple([x * 255 for x in color]) for color in colors] -# colorized_mask = pcv.visualize.colorize_masks(masks_, colors_) -# masked_image = pcv.visualize.overlay_two_imgs(image, colorized_mask, alpha=0.5) -# -# # masked_image = image.astype(np.uint32).copy() -# for i in range(num_insts): -# color = colors[i] -# -# # Mask -# mask = masks[:, :, i] -# # masked_image = _apply_mask(masked_image, mask, color) -# -# ys, xs = np.where(mask > 0) -# x1, x2 = min(xs), max(xs) -# y1, y2 = min(ys), max(ys) -# if show_bbox: -# p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2, alpha=0.7, linestyle="dashed", -# edgecolor=color, facecolor='none') -# ax.add_patch(p) -# -# # Mask Polygon -# # Pad to ensure proper polygons for masks that touch image edges. -# padded_mask = np.zeros( -# (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8) -# padded_mask[1:-1, 1:-1] = mask -# contours = find_contours(padded_mask, 0.5) -# for verts in contours: -# # Subtract the padding and flip (y, x) to (x, y) -# verts = np.fliplr(verts) - 1 -# p = Polygon(verts, facecolor="none", edgecolor=color) -# ax.add_patch(p) -# if not captions: -# caption = str(i) -# else: -# caption = captions[i] -# ax.text(x1, y1 + 8, caption, -# color='w', size=13, backgroundcolor="none") -# ax.imshow(masked_image.astype(np.uint8)) -# return masked_image, colors - -# former definition of this function, relies on the definition of the local funciton "_apply_mask" +# brightness = 1.0 if bright else 0.7 +# hsv = [(i / num, 1, brightness) for i in range(num)] +# colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) +# random.shuffle(colors) +# return colors + def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): """ This function is inspired by the same function used in mrcnn, showing different instances with different colors on top of the original image @@ -140,6 +61,12 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= :return:masked_image :return:colors: colors used to show the instances (same as number of instances) """ + + params.device += 1 + + debug = params.debug + params.debug = None + if image.shape[0:2] != masks.shape[0:2]: fatal_error("Sizes of image and mask mismatch!") # @@ -150,7 +77,15 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= num_insts = masks.shape[2] # Generate random colors - colors = colors or _random_colors(num_insts) + # colors = colors or _random_colors(num_insts) + + if colors is not None: + if max(max(colors)) > 1 or min(min(colors)) < 0: + fatal_error("RGBA values should be within 0-1 range!") + else: + colors_ = pcv.color_palette(num_insts) + colors = [tuple([ci / 255 for ci in c]) for c in colors_] + if len(colors) < num_insts: fatal_error("Not enough colors provided to show all instances!") if len(colors) > num_insts: @@ -164,6 +99,7 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= ax.set_title(title) masked_image = image.astype(np.uint32).copy() + for i in range(num_insts): color = colors[i] @@ -175,14 +111,12 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= x1, x2 = min(xs), max(xs) y1, y2 = min(ys), max(ys) if show_bbox: - p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2, alpha=0.7, linestyle="dashed", - edgecolor=color, facecolor='none') + p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2, alpha=0.7, linestyle="dashed", edgecolor=color, facecolor='none') ax.add_patch(p) # Mask Polygon # Pad to ensure proper polygons for masks that touch image edges. - padded_mask = np.zeros( - (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8) + padded_mask = np.zeros((mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8) padded_mask[1:-1, 1:-1] = mask contours = find_contours(padded_mask, 0.5) for verts in contours: @@ -194,7 +128,15 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= caption = str(i) else: caption = captions[i] - ax.text(x1, y1 + 8, caption, - color='w', size=13, backgroundcolor="none") - ax.imshow(masked_image.astype(np.uint8)) + ax.text(x1, y1 + 8, caption, color='w', size=13, backgroundcolor="none") + + params.debug = debug + if params.debug is not None: + if params.debug == "plot": + ax.imshow(masked_image) + + if params.debug == "print": + ax.imshow(masked_image.astype(np.uint8)) + plt.savefig(os.path.join(params.debug_outdir, str(params.device) + "_displayed_instances.png")) + plt.close("all") return masked_image, colors From 38b98885bc5a352e431c7910782059bba12acdc5 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Thu, 18 Mar 2021 18:48:59 -0500 Subject: [PATCH 12/24] Update tests.py --- tests/tests.py | 27 ++++++++++++++------------- 1 file changed, 14 insertions(+), 13 deletions(-) diff --git a/tests/tests.py b/tests/tests.py index 3e6c1fb30..e8006704c 100755 --- a/tests/tests.py +++ b/tests/tests.py @@ -6232,17 +6232,23 @@ def test_plantcv_visualize_display_instances(tmpdir): img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] - _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, - show_bbox=True) + pcv.params.debug = "plot" + _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True) + assert len(colors) == masks.shape[2] + pcv.params.debug = "print" + cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_visualize_display_instances") + os.mkdir(cache_dir) + pcv.params.debug_outdir = cache_dir + _, colors = pcv.visualize.display_instances(img[:,:,0], masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True) assert len(colors) == masks.shape[2] -def test_plantcv_visualize_display_instances_captions(tmpdir): +def test_plantcv_visualize_display_instances_captions(tmpdir): + pcv.params.debug = None img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] captions = [str(i) for i in range(masks.shape[2])] - _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=captions, - show_bbox=True) + _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=captions, show_bbox=True) assert len(colors) == masks.shape[2] @@ -6256,8 +6262,7 @@ def test_plantcv_visualize_display_instances_bad_color(tmpdir): colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) random.shuffle(colors) with pytest.raises(RuntimeError): - _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, - show_bbox=True) + _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, show_bbox=True) def test_plantcv_visualize_display_instances_bad_color2(tmpdir): import colorsys @@ -6268,8 +6273,7 @@ def test_plantcv_visualize_display_instances_bad_color2(tmpdir): hsv = [(i / num, 1, 1.0) for i in range(num)] colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) random.shuffle(colors) - _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, - show_bbox=True) + _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, show_bbox=True) assert len(colors) == masks.shape[2] def test_plantcv_visualize_display_instances_bad_size(tmpdir): @@ -6277,10 +6281,7 @@ def test_plantcv_visualize_display_instances_bad_size(tmpdir): img = img[0:100,0:100,:] masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] with pytest.raises(RuntimeError): - _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, - show_bbox=True) - - + _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True) # ############################## # Tests for the utils subpackage From 26d647f40d8be1f387ac1a0a69fb5a65dd7a8898 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Thu, 18 Mar 2021 19:29:56 -0500 Subject: [PATCH 13/24] Update tests.py --- tests/tests.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/tests/tests.py b/tests/tests.py index e8006704c..7bec6b489 100755 --- a/tests/tests.py +++ b/tests/tests.py @@ -6264,6 +6264,11 @@ def test_plantcv_visualize_display_instances_bad_color(tmpdir): with pytest.raises(RuntimeError): _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, show_bbox=True) + colors_ = pcv.color_palette(num) + colors = [tuple(c) for c in colors_] + with pytest.raises(RuntimeError): + _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, show_bbox=True) + def test_plantcv_visualize_display_instances_bad_color2(tmpdir): import colorsys import random From cbe1dd4c28d91f9d1396d306c71cbbfa503c16bf Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 28 Apr 2021 10:16:11 -0500 Subject: [PATCH 14/24] Update display_instances.py --- .../plantcv/visualize/display_instances.py | 124 +++++++++--------- 1 file changed, 65 insertions(+), 59 deletions(-) diff --git a/plantcv/plantcv/visualize/display_instances.py b/plantcv/plantcv/visualize/display_instances.py index 881fd63cf..bd4fa20a5 100644 --- a/plantcv/plantcv/visualize/display_instances.py +++ b/plantcv/plantcv/visualize/display_instances.py @@ -8,66 +8,70 @@ import numpy as np from matplotlib import patches, lines from matplotlib.patches import Polygon -from plantcv import plantcv as pcv -from plantcv.plantcv import fatal_error -from plantcv.plantcv import params -from plantcv.plantcv import plot_image -from plantcv.plantcv import print_image +from plantcv.plantcv import fatal_error, params, color_palette import os -def _overlay_mask_on_image(image, mask, color, alpha=0.5): - """ apply a mask to an input image with a user defined color - :param image: input RGB or grayscale image - :param mask: desired mask - :param color: (a tuple) desired color to show the mask on top of the image - :param alpha: (a value between 0 and 1) transparency value when blending mask and image, by default 0.5 - :return: image with an mask with desired color on top of it - """ - if len(image.shape) == 2: - image = cv2.cvtColor(image.astype(np.uint8), cv2.COLOR_GRAY2BGR) - for c in range(image.shape[-1]): - image[:, :, c] = np.where(mask == 1, - image[:, :, c] * - (1 - alpha) + alpha * color[c] * 255, - image[:, :, c]) - return image - -# def _random_colors(num, bright=True): -# """ -# Generate desired number of random colors. To get visually distinct colors, generate them in HSV space then convert to RGB. -# :param num: number of colors to be generated -# :param bright: True or False, if true, the brightness would be 1.0; if False, the brightness would be 0.7. By default it would be True (brightness 0.7) -# :return: generated colors (a list of tuples) -# """ -# -# brightness = 1.0 if bright else 0.7 -# hsv = [(i / num, 1, brightness) for i in range(num)] -# colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) -# random.shuffle(colors) -# return colors - -def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True): + +def _overlay_mask_on_img(img, mask, color, alpha=0.5): + """ Overlay a given mask on top of an image such that the masked area (the non-zero areas in the mask) is shown in user + defined color, the other area (the zero-valued areas in the mask) is shown in original image. + Inputs: + img = image to show, can be either visible or grayscale + mask = mask to be put on top of the image + color = a tuple of desired color to show the mask on top of the image + alpha = a value (between 0 and 1) indicating the transparency when blending mask and image, by default 0.5 + Output: + img = the original image with mask overlaied on top + + :param img: numpy.ndarray + :param mask: numpy.ndarray + :param color: tuple + :param alpha: float + :return: img: numpy.ndarray """ + if len(img.shape) == 2: + img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) + for c in range(img.shape[-1]): + img[:, :, c] = np.where(mask == 1, + img[:, :, c] * + (1 - alpha) + alpha * color[c] * 255, + img[:, :, c]) + return img + + +def display_instances(img, masks, figsize=(16, 16), title="", colors=None, captions=None, show_bbox=True, ax=None): + """ Display multiple instances in image based on the given masks This function is inspired by the same function used in mrcnn, showing different instances with different colors on top of the original image Users also have the option to specify the color for every instance, as well as the caption for every instance. Showing bounding boxes is another option. - :param image: (required, ndarray) - :param masks: (required, ndarray) - :param figsize: (optional, tuple) the size of the generated figure - :param title: (optional, str) the title of the figure - :param ax: (optional, matplotlib.axes._subplots.AxesSubplot) the axis to plot on. If no axis is passed, create one and automatically call show() - :param colors: (optional, list of tuples, every value should be in the range of [0.0,1.0]) a list of colors to use with each object. If no value is passed, a set of random colors would be used - :param captions: (optional, str) a list of strings to use as captions for each object. If no list of captions is provided, show the local index of the instance - :param show_bbox: (optional, bool) indicator of whether showing the bounding-box - :return:masked_image - :return:colors: colors used to show the instances (same as number of instances) + Inputs: + img = rgb image to show + mask = a bunch of masks in a matrix + figsize = desired size of figure, by default (16,16) + title = desired title to show, by default "" + colors = a list of colors for every instance to display, by default colors=None + captions = a list of names for every instance, by default captions=None + show_bbox = a flog indicating whether show bounding box, by default show_bbox=True + ax = axis to show, by default ax=None + Outputs: + masked_img = image with instances masks overlaied on top + colors = colors used to display every instance + + :param img: numpy.ndarray + :param masks: numpy.ndarray + :param figsize: tuple + :param title: str + :param colors: list (of tuples) + :param captions: str + :param show_bbox: bool + :param ax: + :return: masked_img: numpy.ndarray + :return: colors: list (of tuples) """ - params.device += 1 - debug = params.debug params.debug = None - if image.shape[0:2] != masks.shape[0:2]: + if img.shape[0:2] != masks.shape[0:2]: fatal_error("Sizes of image and mask mismatch!") # # auto_show = False @@ -76,14 +80,15 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= # auto_show = True num_insts = masks.shape[2] - # Generate random colors + + # # Generate random colors # colors = colors or _random_colors(num_insts) if colors is not None: if max(max(colors)) > 1 or min(min(colors)) < 0: fatal_error("RGBA values should be within 0-1 range!") else: - colors_ = pcv.color_palette(num_insts) + colors_ = color_palette(num_insts) colors = [tuple([ci / 255 for ci in c]) for c in colors_] if len(colors) < num_insts: @@ -92,20 +97,19 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= colors = colors[0:num_insts] # Show area outside image boundaries. - height, width = image.shape[:2] + height, width = img.shape[:2] ax.set_ylim(height + 10, -10) ax.set_xlim(-10, width + 10) ax.axis('off') ax.set_title(title) - masked_image = image.astype(np.uint32).copy() - + masked_img = img.astype(np.uint32).copy() for i in range(num_insts): color = colors[i] # Mask mask = masks[:, :, i] - masked_image = _overlay_mask_on_image(masked_image, mask, color) + masked_img = _overlay_mask_on_img(masked_img, mask, color) ys, xs = np.where(mask > 0) x1, x2 = min(xs), max(xs) @@ -130,13 +134,15 @@ def display_instances(image, masks, figsize=(16, 16), title="", ax=None, colors= caption = captions[i] ax.text(x1, y1 + 8, caption, color='w', size=13, backgroundcolor="none") + masked_img = masked_img.astype(np.uint8) params.debug = debug if params.debug is not None: if params.debug == "plot": - ax.imshow(masked_image) + ax.imshow(masked_img) if params.debug == "print": - ax.imshow(masked_image.astype(np.uint8)) + ax.imshow(masked_img) plt.savefig(os.path.join(params.debug_outdir, str(params.device) + "_displayed_instances.png")) plt.close("all") - return masked_image, colors + + return masked_img, colors From 0a611710cc447b1b4cf39521226bfcac3b976777 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 28 Apr 2021 10:16:14 -0500 Subject: [PATCH 15/24] Update tests.py --- tests/tests.py | 86 ++++++++++++++++++++++---------------------------- 1 file changed, 37 insertions(+), 49 deletions(-) diff --git a/tests/tests.py b/tests/tests.py index 20e6a8e0e..f6d3ffdc7 100755 --- a/tests/tests.py +++ b/tests/tests.py @@ -20,6 +20,7 @@ import dask from dask.distributed import Client import pickle as pkl +from skimage.util import img_as_ubyte PARALLEL_TEST_DATA = os.path.join(os.path.dirname(os.path.abspath(__file__)), "parallel_data") TEST_TMPDIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", ".cache") @@ -6362,65 +6363,52 @@ def test_plantcv_visualize_overlay_two_imgs_size_mismatch(): with pytest.raises(RuntimeError): _ = pcv.visualize.overlay_two_imgs(img1=img1, img2=img2) -def test_plantcv_visualize_display_instances(tmpdir): - - img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") - masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] - pcv.params.debug = "plot" - _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True) - assert len(colors) == masks.shape[2] - pcv.params.debug = "print" +def test_plantcv_visualize_display_instances(): cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_visualize_display_instances") os.mkdir(cache_dir) + # create synthetic test data + img = img_as_ubyte(np.random.rand(10,10,3)) + masks = np.zeros((10, 10, 2)) + masks[1:3, 3:5, 0] = 1 + masks[2:5, 1:3, 1] = 1 + colors = [(1.0,0.0,0.15),(1.0,0.0,0.74)] + pcv.params.debug = "plot" + _, ax = plt.subplots(1, 1, figsize=(16, 16)) + _, colors = pcv.visualize.display_instances(img, masks, title="test", colors=colors, captions=['1','2'], show_bbox=True, ax=ax) + pcv.params.debug = "print" pcv.params.debug_outdir = cache_dir - _, colors = pcv.visualize.display_instances(img[:,:,0], masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True) + _, colors = pcv.visualize.display_instances(img, masks) assert len(colors) == masks.shape[2] - -def test_plantcv_visualize_display_instances_captions(tmpdir): +def test_plantcv_visualize_display_instances_bad_color(): pcv.params.debug = None - img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") - masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] - captions = [str(i) for i in range(masks.shape[2])] - _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=captions, show_bbox=True) - assert len(colors) == masks.shape[2] - + # create synthetic test data + img = img_as_ubyte(np.random.rand(10,10,3)) + masks = np.zeros((10, 10, 2), dtype=np.uint8) + masks[1:3, 3:5, 0] = 1 + masks[2:5, 1:3, 1] = 1 + colors = [(1.0,0.0,0.15)] + with pytest.raises(RuntimeError): + _, _ = pcv.visualize.display_instances(img, masks, colors=colors) -def test_plantcv_visualize_display_instances_bad_color(tmpdir): - import colorsys - import random - img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") - masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] - num = 2 - hsv = [(i / num, 1, 1.0) for i in range(num)] - colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) - random.shuffle(colors) - with pytest.raises(RuntimeError): - _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, show_bbox=True) - - colors_ = pcv.color_palette(num) - colors = [tuple(c) for c in colors_] - with pytest.raises(RuntimeError): - _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, show_bbox=True) - -def test_plantcv_visualize_display_instances_bad_color2(tmpdir): - import colorsys - import random - img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") - masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] - num = 20 - hsv = [(i / num, 1, 1.0) for i in range(num)] - colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv)) - random.shuffle(colors) - _, colors = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=colors, captions=None, show_bbox=True) +def test_plantcv_visualize_display_instances_bad_color2(): + pcv.params.debug = None + # create synthetic test data + img = img_as_ubyte(np.random.rand(10,10,3)) + masks = np.zeros((10, 10, 2), dtype=np.uint8) + masks[1:3, 3:5, 0] = 1 + masks[2:5, 1:3, 1] = 1 + colors = [(1.0,0.0,0.15),(1.0,0.0,0.74),(0.0,1.0,0.74)] + _, colors = pcv.visualize.display_instances(img, masks, colors=colors) assert len(colors) == masks.shape[2] -def test_plantcv_visualize_display_instances_bad_size(tmpdir): - img,_,_ = pcv.readimage(filename=os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_IMG),mode="RGB") - img = img[0:100,0:100,:] - masks = pkl.load(open(os.path.join(TEST_DATA,TEST_INPUT_INSTANCE_MASK), "rb"))["masks"] +def test_plantcv_visualize_display_instances_bad_size(): + pcv.params.debug = None + # create synthetic test data + img = img_as_ubyte(np.random.rand(5,5,3)) + masks = np.zeros((10, 10, 2), dtype=np.uint8) with pytest.raises(RuntimeError): - _, _ = pcv.visualize.display_instances(img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True) + _, _ = pcv.visualize.display_instances(img, masks) # ############################## # Tests for the utils subpackage From 53477c4ce4cce5e08c0fd2c815d0c3afff3574c4 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 28 Apr 2021 10:16:17 -0500 Subject: [PATCH 16/24] Update __init__.py --- plantcv/plantcv/visualize/__init__.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/plantcv/plantcv/visualize/__init__.py b/plantcv/plantcv/visualize/__init__.py index e0f0e2b1a..d435aaa87 100644 --- a/plantcv/plantcv/visualize/__init__.py +++ b/plantcv/plantcv/visualize/__init__.py @@ -5,7 +5,8 @@ from plantcv.plantcv.visualize.colorspaces import colorspaces from plantcv.plantcv.visualize.auto_threshold_methods import auto_threshold_methods from plantcv.plantcv.visualize.overlay_two_imgs import overlay_two_imgs +from plantcv.plantcv.visualize.overlay_mask_on_img import overlay_mask_on_img from plantcv.plantcv.visualize.display_instances import display_instances __all__ = ["pseudocolor", "colorize_masks", "histogram", "clustered_contours", "colorspaces", "auto_threshold_methods", - "overlay_two_imgs","display_instances"] + "overlay_two_imgs","overlay_mask_on_img","display_instances"] From aef9932b2d33445e295f530abdfcd9b250c965ac Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 28 Apr 2021 10:27:44 -0500 Subject: [PATCH 17/24] Merge branch 'master' into visualize_show_instances --- plantcv/utils/sample_images.py | 44 +++++++++++++--------------------- 1 file changed, 16 insertions(+), 28 deletions(-) diff --git a/plantcv/utils/sample_images.py b/plantcv/utils/sample_images.py index 5d5f175ce..d99ad3444 100644 --- a/plantcv/utils/sample_images.py +++ b/plantcv/utils/sample_images.py @@ -6,14 +6,12 @@ def sample_images(source_path, dest_path, num=100): if not os.path.exists(source_path): - raise IOError("Directory does not exist: {0}".format(source_path)) + raise IOError(f"Directory does not exist: {source_path}") if not os.path.exists(dest_path): os.makedirs(dest_path) # exist_ok argument does not exist in python 2 img_element_array = [] - sample_array = [] - num_images = [] img_extensions = ['.png', '.jpg', '.jpeg', '.tif', '.tiff', '.gif'] # If SnapshotInfo exists then need to make a new csv for the random image sample @@ -31,22 +29,19 @@ def sample_images(source_path, dest_path, num=100): # Check to make sure number of imgs to select is less than number of images found if num > len(line_array): - fatal_error("Number of images found ({0}) less than 'num'.". - format(len(line_array))) - - for i in range(0, num): - r = random.randint(0, len(line_array) - 1) - while r in num_images: - r = random.randint(0, len(line_array) - 1) - sample_array.append(line_array[r]) - num_images.append(r) + fatal_error(f"Number of images found ({len(line_array)}) less than 'num'.") + # Create SnapshotInfo file out_file = open(os.path.join(dest_path, 'SnapshotInfo.csv'), 'w') out_file.write(header) - for element in sample_array: - out_file.write(','.join(element)) - snap_path = os.path.join(source_path, "snapshot" + element[1]) - folder_path = os.path.join(dest_path, "snapshot" + element[1]) + + # Get random snapshots + random_index = random.sample(range(0, len(line_array) - 1), num) + for i in random_index: + row = line_array[int(i)] + out_file.write(','.join(row)) + snap_path = os.path.join(source_path, "snapshot" + row[1]) + folder_path = os.path.join(dest_path, "snapshot" + row[1]) if not os.path.exists(folder_path): os.mkdir(folder_path) # the beginning of folder_path (dest_path) already exists from above for root, dirs, files in os.walk(snap_path): @@ -58,21 +53,14 @@ def sample_images(source_path, dest_path, num=100): # Check file type so that only images get copied over name, ext = os.path.splitext(file) if ext.lower() in img_extensions: - img_element_array.append(os.path.join(root,file)) + img_element_array.append(os.path.join(root, file)) # Check to make sure number of imgs to select is less than number of images found if num > len(img_element_array): - fatal_error("Number of images found ({0}) less than 'num'.". - format(len(img_element_array))) + fatal_error(f"Number of images found ({len(img_element_array)}) less than 'num'.") # Get random images - for i in range(0, num): - r = random.randint(0, len(img_element_array) - 1) - while r in num_images: - r = random.randint(0, len(img_element_array) - 1) - sample_array.append(img_element_array[r]) - num_images.append(r) - + random_index = random.sample(range(0, len(img_element_array) - 1), num) # Copy images over to destination - for element in sample_array: - shutil.copy(element, dest_path) + for i in random_index: + shutil.copy(img_element_array[int(i)], dest_path) From 688e6aacc428b99614c35ea5ca49e7cdb14e0053 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 28 Apr 2021 10:32:25 -0500 Subject: [PATCH 18/24] Update __init__.py --- plantcv/plantcv/visualize/__init__.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/plantcv/plantcv/visualize/__init__.py b/plantcv/plantcv/visualize/__init__.py index d435aaa87..e0f0e2b1a 100644 --- a/plantcv/plantcv/visualize/__init__.py +++ b/plantcv/plantcv/visualize/__init__.py @@ -5,8 +5,7 @@ from plantcv.plantcv.visualize.colorspaces import colorspaces from plantcv.plantcv.visualize.auto_threshold_methods import auto_threshold_methods from plantcv.plantcv.visualize.overlay_two_imgs import overlay_two_imgs -from plantcv.plantcv.visualize.overlay_mask_on_img import overlay_mask_on_img from plantcv.plantcv.visualize.display_instances import display_instances __all__ = ["pseudocolor", "colorize_masks", "histogram", "clustered_contours", "colorspaces", "auto_threshold_methods", - "overlay_two_imgs","overlay_mask_on_img","display_instances"] + "overlay_two_imgs","display_instances"] From accf9557d606d0409166612a7bd3f1f2f8734abb Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 28 Apr 2021 11:04:42 -0500 Subject: [PATCH 19/24] fix RGB -> BGR colors --- plantcv/plantcv/visualize/display_instances.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/plantcv/plantcv/visualize/display_instances.py b/plantcv/plantcv/visualize/display_instances.py index bd4fa20a5..b7867bd3e 100644 --- a/plantcv/plantcv/visualize/display_instances.py +++ b/plantcv/plantcv/visualize/display_instances.py @@ -10,7 +10,7 @@ from matplotlib.patches import Polygon from plantcv.plantcv import fatal_error, params, color_palette import os - +from cv2 import cvtColor, COLOR_BGR2RGB def _overlay_mask_on_img(img, mask, color, alpha=0.5): """ Overlay a given mask on top of an image such that the masked area (the non-zero areas in the mask) is shown in user @@ -71,6 +71,9 @@ def display_instances(img, masks, figsize=(16, 16), title="", colors=None, capti debug = params.debug params.debug = None + # Auto-increment the device counter + params.device += 1 + if img.shape[0:2] != masks.shape[0:2]: fatal_error("Sizes of image and mask mismatch!") # @@ -109,7 +112,8 @@ def display_instances(img, masks, figsize=(16, 16), title="", colors=None, capti # Mask mask = masks[:, :, i] - masked_img = _overlay_mask_on_img(masked_img, mask, color) + # the color is in order of r-g-b, however the image is in order of b-g-r, so take the reverse of color + masked_img = _overlay_mask_on_img(masked_img, mask, color[::-1]) ys, xs = np.where(mask > 0) x1, x2 = min(xs), max(xs) @@ -134,7 +138,7 @@ def display_instances(img, masks, figsize=(16, 16), title="", colors=None, capti caption = captions[i] ax.text(x1, y1 + 8, caption, color='w', size=13, backgroundcolor="none") - masked_img = masked_img.astype(np.uint8) + masked_img = cvtColor(masked_img.astype(np.uint8), COLOR_BGR2RGB) params.debug = debug if params.debug is not None: if params.debug == "plot": From 347a1219f2f8e04a311efdacfea48010f2efeeaf Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 28 Apr 2021 11:05:03 -0500 Subject: [PATCH 20/24] upload new doc image --- .../visualize_display_instances/result1.png | Bin 74832 -> 81161 bytes .../visualize_display_instances/result2.png | Bin 301759 -> 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2021 11:05:24 -0500 Subject: [PATCH 21/24] Update visualize_display_instances.md --- docs/visualize_display_instances.md | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/docs/visualize_display_instances.md b/docs/visualize_display_instances.md index 548e65944..57ddf5f87 100644 --- a/docs/visualize_display_instances.md +++ b/docs/visualize_display_instances.md @@ -2,7 +2,7 @@ This function displays different object intances in different colors on top of the original image. -**plantcv.visualize.display_instances**(*img, masks, figsize=(16, 16), title="", ax=None, colors=None, captions=None, show_bbox=True*) +**plantcv.visualize.display_instances**(*img, masks, figsize=(16, 16), title="", colors=None, captions=None, show_bbox=True, ax=None*) **returns** masked_img, colors - **Parameters:** @@ -10,11 +10,10 @@ This function displays different object intances in different colors on top of t - masks - (required, ndarray) instance masks represented by a 3-d array, the 3rd dimension represents the number of insatnces to show. - figsize - (optional, tuple) the size of the generated figure - title - (optional, str) the title of the figure - - ax - (optional, matplotlib.axes._subplots.AxesSubplot) the axis to plot on. If no axis is passed, create one and automatically call show()) - colors - (optional, list of tuples, every value should be in the range of [0.0,1.0]) a list of colors to use with each object. If no value is passed, a set of random colors would be used - captions - (optional, str) a list of strings to use as captions for each object. If no list of captions is provided, show the local index of the instance - show_bbox - (optional, bool) indicator of whether showing the bounding-box - + - ax - (optional, matplotlib.axes._subplots.AxesSubplot) the axis to plot on. If no axis is passed, a new one will be created - **Context:** - Used to display different segmented instances on top of the original image. - **Example use:** @@ -24,7 +23,7 @@ This function displays different object intances in different colors on top of t ![Screenshot](img/documentation_images/visualize_display_instances/visualize_inst_seg_img.png) -**masks: 10 different segmentation masks represent for different leaves** +**masks: 10 segmentation masks represent for different leaves** ![Screenshot](img/documentation_images/visualize_display_instances/mask_0.png) ![Screenshot](img/documentation_images/visualize_display_instances/mask_1.png) From c14785b6f9b716ae028d2a062409240c7323bec8 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 28 Apr 2021 11:41:58 -0500 Subject: [PATCH 22/24] Update display_instances.py --- plantcv/plantcv/visualize/display_instances.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/plantcv/plantcv/visualize/display_instances.py b/plantcv/plantcv/visualize/display_instances.py index b7867bd3e..2af31fae5 100644 --- a/plantcv/plantcv/visualize/display_instances.py +++ b/plantcv/plantcv/visualize/display_instances.py @@ -29,8 +29,8 @@ def _overlay_mask_on_img(img, mask, color, alpha=0.5): :param alpha: float :return: img: numpy.ndarray """ - if len(img.shape) == 2: - img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) + # if len(img.shape) == 2: + # img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) for c in range(img.shape[-1]): img[:, :, c] = np.where(mask == 1, img[:, :, c] * From eafaa6a43b6a991ebf7333078e47c72c6e658339 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Wed, 28 Apr 2021 11:42:00 -0500 Subject: [PATCH 23/24] Update tests.py --- tests/tests.py | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/tests/tests.py b/tests/tests.py index f6d3ffdc7..d341fbdb0 100755 --- a/tests/tests.py +++ b/tests/tests.py @@ -6402,6 +6402,17 @@ def test_plantcv_visualize_display_instances_bad_color2(): _, colors = pcv.visualize.display_instances(img, masks, colors=colors) assert len(colors) == masks.shape[2] +def test_plantcv_visualize_display_instances_bad_color3(): + pcv.params.debug = None + # create synthetic test data + img = img_as_ubyte(np.random.rand(10,10,3)) + masks = np.zeros((10, 10, 2), dtype=np.uint8) + masks[1:3, 3:5, 0] = 1 + masks[2:5, 1:3, 1] = 1 + colors = [(10,0.0,15.0),(10,0.0,74)] + with pytest.raises(RuntimeError): + _, _ = pcv.visualize.display_instances(img, masks, colors=colors) + def test_plantcv_visualize_display_instances_bad_size(): pcv.params.debug = None # create synthetic test data @@ -6410,6 +6421,7 @@ def test_plantcv_visualize_display_instances_bad_size(): with pytest.raises(RuntimeError): _, _ = pcv.visualize.display_instances(img, masks) + # ############################## # Tests for the utils subpackage # ############################## From 7979d0e3ef42936256ecee4218d63210477a6007 Mon Sep 17 00:00:00 2001 From: Hudanyun Sheng Date: Tue, 17 Aug 2021 16:01:56 -0500 Subject: [PATCH 24/24] Merge remote-tracking branch 'origin/master' into visualize_show_instances --- plantcv/plantcv/hyperspectral/read_data.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/plantcv/plantcv/hyperspectral/read_data.py b/plantcv/plantcv/hyperspectral/read_data.py index cf5bc603c..7c0c1ec97 100644 --- a/plantcv/plantcv/hyperspectral/read_data.py +++ b/plantcv/plantcv/hyperspectral/read_data.py @@ -118,6 +118,7 @@ def read_data(filename): hdata = hdata.replace("{\n", "{") hdata = hdata.replace("\n}", "}") hdata = hdata.replace(" \n ", "") + hdata = hdata.replace(" \n", "") hdata = hdata.replace(";", "") hdata = hdata.split("\n") @@ -125,9 +126,11 @@ def read_data(filename): for i, string in enumerate(hdata): if ' = ' in string: header_data = string.split(" = ") + header_data[0] = header_data[0].lower() header_dict.update({header_data[0].rstrip(): header_data[1].rstrip()}) elif ' : ' in string: header_data = string.split(" : ") + header_data[0] = header_data[0].lower() header_dict.update({header_data[0].rstrip(): header_data[1].rstrip()}) # Reformat wavelengths

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