33 napari extract and format data for naive bayes

docs/changelog.md

@@ -18,6 +18,10 @@ All notable changes to this project will be documented below.
 
 * v0.1dev: viewer = **annotate.napari_label_classes**(*img, classes, size=10, importdata=False, show=True*)
 
+#### annotate.napari_naive_bayes_colors
+
+* v0.1dev: viewer = **annotate.napari_naive_bayes_colors**(*img, maskdict, filename*)
+
 #### annotate.napari_open
 
 * v0.1dev: viewer = **annotate.napari_open**(*img, mode = 'native', show=True*)

docs/napari_naive_bayes_colors.md

@@ -0,0 +1,53 @@
+## Extract Color Data from Dictionary of Masks for Naive Bayes
+
+This function is to extract color information from a dictionary of masks in order
+to get data for naive bayes functions. Collect pixel training data in Napari, rather than ImageJ for example. 
+
+**plantcv.annotate.napari_naive_bayes_colors**(*img, maskdict, filename*)
+
+**returns** data frame
+
+- **Parameters:**
+    - img - RGB image to extract color information from
+    - maskdict - dictionary of masks, output of [`napari_points_mask`](docs/napari_points_mask.md) for example
+    - filename - filename to save data, formatted to work with [Naive Bayes segmentation](https://plantcv.readthedocs.io/en/latest/tutorials/machine_learning_tutorial/)
+
+- **Context:**
+    - This function is used to extract color information from an RGB image and a mask and convert data 
+    to be compatible with Naive Bayes training functions. 
+
+- **Example use:**
+    - used in Napari Naive Bayes
+
+
+```python
+import plantcv.plantcv as pcv 
+import plantcv.annotate as pcvan
+from plantcv import learn
+import napari
+
+# Create an instance of the Points class
+img, path, name = pcv.readimage("./wheat.png")
+
+# Should open interactive napari viewer
+viewer = pcvan.napari_label_classes(img=img, classes=['background','healthy', 'rust', 'chlorosis'], size=4)
+
+maskdict = pcvan.napari_points_mask(img, viewer)
+
+nbdata = pcvan.napari_naive_bayes_colors(img=img, maskdict=maskdict, filename="./nbdata.txt")
+
+learn.naive_bayes_multiclass(samples_file="./nbdata.txt", outfile="naive_bayes_test_pdfs.txt")
+
+masks = pcv.naive_bayes_classifier(rgb_img=img, 
+                                   pdf_file="./naive_bayes_test_pdfs.txt")
+
+```
+
+![Screenshot](img/documentation_images/napari_points_mask/viewer_labeled.png)
+
+***Output Data***
+
+![Screenshot](img/documentation_images/napari_naive_bayes_colors/nbdata.png)
+
+
+**Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annotate/napari_naive_bayes_colors.py)

mkdocs.yml

@@ -20,6 +20,7 @@ nav:
       - Napari Classes: napari_classes.md
       - Napari Join: napari_join_labels.md
       - Napari Label: napari_label_classes.md
+      - Napari Naive Bayes: napari_naive_bayes_colors.md
       - Napari Open: napari_open.md
       - Napari Points Mask: napari_points_mask.md
       - Napari Read Coor: napari_read_coor.md

plantcv/annotate/__init__.py

@@ -8,6 +8,7 @@
 from plantcv.annotate.napari_save_coor import napari_save_coor
 from plantcv.annotate.napari_read_coor import napari_read_coor
 from plantcv.annotate.napari_points_mask import napari_points_mask
+from plantcv.annotate.napari_naive_bayes_colors import napari_naive_bayes_colors
 
 # Auto versioning
 __version__ = version("plantcv-annotate")
@@ -21,5 +22,6 @@
     "napari_join_labels",
     "napari_save_coor",
     "napari_read_coor",
-    "napari_points_mask"
+    "napari_points_mask",
+    "napari_naive_bayes_colors"
 ]

plantcv/annotate/napari_naive_bayes_colors.py

@@ -0,0 +1,40 @@
+# Get Data from Dictionary of Masks and Format for Naive Bayes
+
+import pandas as pd
+import numpy as np
+
+
+def napari_naive_bayes_colors(img, maskdict, filename):
+    """
+    get names of napari keys
+
+    Inputs:
+    img  = rgb image
+    maskdict = dictionary of masks, output of napari_points_mask for example
+    filename = name/path of file to save data
+
+    Returns:
+    dataarray  = pandas data array
+
+    :param img: RGB image
+    :param maskdict = dictionary of masks
+    :param filename = str
+    :return dataarray: pandas dataframe
+    """
+    keys = list(maskdict.keys())
+    datadict = {}
+    for key in keys:
+        mask = maskdict[key]
+        nonzero = np.transpose(np.nonzero(mask))
+        keydata = []
+        for x, y in nonzero:
+            rgbdata = list(reversed(img[x][y]))
+            rgblist = ", ".join(repr(int(e)) for e in rgbdata)
+            keydata.append(rgblist)
+        dict1 = {key: keydata}
+        datadict.update(dict1)
+    dataarray = pd.DataFrame.from_dict(datadict, orient='index')
+    datatranspose = dataarray.transpose()
+    datatranspose.to_csv(filename, sep="\t", index=False)
+
+    return datatranspose

tests/conftest.py

@@ -28,6 +28,11 @@ def __init__(self):
         # Coordinates File
         filename_coor = "germinated.txt"
         self.coor_data = os.path.join(self.datadir, filename_coor)
+        # Naive Bayes Data
+        filename_nbrgb = "08_02_16-QTHJ-RIL-019_zoomed.png"
+        self.nb_rgb = os.path.join(self.datadir, filename_nbrgb)
+        filename_nbmask = "my_maskdict.npy"
+        self.nb_mask = os.path.join(self.datadir, filename_nbmask)
 
 
 

tests/test_napari_naive_bayes.py

@@ -0,0 +1,16 @@
+import os
+import numpy as np
+from plantcv.plantcv import readimage
+from plantcv.annotate import napari_naive_bayes_colors
+
+
+def test_napari_naive_bayes_colors(test_data, tmpdir):
+    """Test for PlantCV.Annotate"""
+    # Read in test data
+    cache_dir = tmpdir.mkdir("cache")
+    img, _, _ = readimage(test_data.nb_rgb)
+    maskdict = np.load(test_data.nb_mask, allow_pickle='TRUE').item()
+    filename = os.path.join(cache_dir, 'tempfile.txt')
+    data = napari_naive_bayes_colors(img, maskdict, filename)
+
+    assert data.shape == (16, 1)