update docs and minor tweaks

Author: zsylvester

docs/source/api_reference.rst

@@ -3,39 +3,43 @@ API Reference
 .. toctree::
    :caption: API Reference
 
-.. autofunction:: segmenteverygrain.predict_image
-.. autofunction:: segmenteverygrain.predict_large_image
-.. autofunction:: segmenteverygrain.predict_image_tile
-.. autofunction:: segmenteverygrain.label_grains
-.. autofunction:: segmenteverygrain.one_point_prompt
-.. autofunction:: segmenteverygrain.two_point_prompt
-.. autofunction:: segmenteverygrain.find_overlapping_polygons
-.. autofunction:: segmenteverygrain.weighted_crossentropy
-.. autofunction:: segmenteverygrain.plot_images_and_labels
 .. autofunction:: segmenteverygrain.calculate_iou
-.. autofunction:: segmenteverygrain.pick_most_similar_polygon
-.. autofunction:: segmenteverygrain.sam_segmentation
-.. autofunction:: segmenteverygrain.find_connected_components
-.. autofunction:: segmenteverygrain.merge_overlapping_polygons
-.. autofunction:: segmenteverygrain.rasterize_grains
+.. autofunction:: segmenteverygrain.classify_points
+.. autofunction:: segmenteverygrain.click_for_scale
+.. autofunction:: segmenteverygrain.collect_polygon_from_mask
+.. autofunction:: segmenteverygrain.compute_curvature
+.. autofunction:: segmenteverygrain.convert_to_large_image_coords
+.. autofunction:: segmenteverygrain.create_and_train_model
 .. autofunction:: segmenteverygrain.create_labeled_image
+.. autofunction:: segmenteverygrain.create_train_val_test_data
+.. autofunction:: segmenteverygrain.extract_patch
+.. autofunction:: segmenteverygrain.find_connected_components
+.. autofunction:: segmenteverygrain.find_grain_size_classes
+.. autofunction:: segmenteverygrain.find_overlapping_polygons
+.. autofunction:: segmenteverygrain.get_area_weighted_distribution
+.. autofunction:: segmenteverygrain.get_grains_from_patches
+.. autofunction:: segmenteverygrain.label_grains
 .. autofunction:: segmenteverygrain.load_and_preprocess
+.. autofunction:: segmenteverygrain.merge_overlapping_polygons
 .. autofunction:: segmenteverygrain.onclick
-.. autofunction:: segmenteverygrain.onpress
 .. autofunction:: segmenteverygrain.onclick2
-.. autofunction:: segmenteverygrain.onpress2
-.. autofunction:: segmenteverygrain.click_for_scale
-.. autofunction:: segmenteverygrain.get_grains_from_patches
-.. autofunction:: segmenteverygrain.plot_image_w_colorful_grains
-.. autofunction:: segmenteverygrain.plot_grain_axes_and_centroids
-.. autofunction:: segmenteverygrain.classify_points
-.. autofunction:: segmenteverygrain.compute_curvature
-.. autofunction:: segmenteverygrain.extract_patch
-.. autofunction:: segmenteverygrain.convert_to_large_image_coords
 .. autofunction:: segmenteverygrain.onclick_large_image
+.. autofunction:: segmenteverygrain.one_point_prompt
+.. autofunction:: segmenteverygrain.onpress
+.. autofunction:: segmenteverygrain.onpress2
 .. autofunction:: segmenteverygrain.patchify_training_data
-.. autofunction:: segmenteverygrain.create_train_val_test_data
-.. autofunction:: segmenteverygrain.create_and_train_model
-.. autofunction:: segmenteverygrain.save_polygons
+.. autofunction:: segmenteverygrain.pick_most_similar_polygon
+.. autofunction:: segmenteverygrain.plot_grain_axes_and_centroids
+.. autofunction:: segmenteverygrain.plot_histogram_of_axis_lengths
+.. autofunction:: segmenteverygrain.plot_image_w_colorful_grains
+.. autofunction:: segmenteverygrain.plot_images_and_labels
+.. autofunction:: segmenteverygrain.predict_image
+.. autofunction:: segmenteverygrain.predict_image_tile
+.. autofunction:: segmenteverygrain.predict_large_image
+.. autofunction:: segmenteverygrain.rasterize_grains
 .. autofunction:: segmenteverygrain.read_polygons
-.. autofunction:: segmenteverygrain.plot_histogram_of_axis_lengths
+.. autofunction:: segmenteverygrain.sam_segmentation
+.. autofunction:: segmenteverygrain.save_polygons
+.. autofunction:: segmenteverygrain.two_point_prompt
+.. autofunction:: segmenteverygrain.Unet
+.. autofunction:: segmenteverygrain.weighted_crossentropy

docs/source/conf.py

@@ -14,7 +14,7 @@
 project = 'segmenteverygrain'
 copyright = '2024, Zoltan Sylvester'
 author = 'Zoltan Sylvester'
-release = '0.1.9'
+release = '0.2.1'
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

segmenteverygrain/Segment_every_grain_colab.ipynb

@@ -794,7 +794,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.15"
+   "version": "3.8.20"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {

segmenteverygrain/Segment_every_grain_w_georeferencing.ipynb

@@ -80,7 +80,6 @@
    "cell_type": "markdown",
    "id": "a3c1dfc6",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -127,7 +126,6 @@
    "cell_type": "markdown",
    "id": "968737c4",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -225,7 +223,6 @@
    "cell_type": "markdown",
    "id": "ab7201a5",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -316,7 +313,6 @@
    "cell_type": "markdown",
    "id": "768a05d2",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -592,7 +588,6 @@
    "cell_type": "markdown",
    "id": "039415c6",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -628,7 +623,6 @@
    "cell_type": "markdown",
    "id": "24f154fb",
    "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [
@@ -1071,7 +1065,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.15"
+   "version": "3.8.20"
   }
  },
  "nbformat": 4,

segmenteverygrain/segmenteverygrain.py

@@ -415,7 +415,6 @@ def Unet():
 
     tf.keras.backend.clear_session()
 
-    # image = tf.keras.Input((256, 256, 3), name='input')
     inputs = Input((256, 256, 3), name='input')
 
     conv1 = Conv2D(16, (3,3), activation='relu', padding = 'same')(inputs)
@@ -1565,7 +1564,7 @@ def patchify_training_data(input_dir, patch_dir):
     start_no = 0
     for image in tqdm(images):
         # Load the large image
-        large_image = tf.keras.preprocessing.image.load_img(image)
+        large_image = load_img(image)
         # Convert the image to a tensor
         large_image = tf.keras.preprocessing.image.img_to_array(large_image)
         # Reshape the tensor to have a batch size of 1
@@ -1591,7 +1590,7 @@ def patchify_training_data(input_dir, patch_dir):
     start_no = 0
     for image in tqdm(labels):
         # Load the large image
-        large_image = tf.keras.preprocessing.image.load_img(image)
+        large_image = load_img(image)
         # Convert the image to a tensor
         large_image = tf.keras.preprocessing.image.img_to_array(large_image)
         large_image = large_image[:,:,0,np.newaxis] # only keep one layer and add a new axis

setup.py

@@ -8,7 +8,7 @@
 
 setuptools.setup(
     name="segmenteverygrain",
-    version="0.2.0",
+    version="0.2.1",
     author="Zoltan Sylvester",
     author_email="zoltan.sylvester@beg.utexas.edu",
     description="a SAM-based model for segmenting grains in images of grains",