diff 2d_feature_extraction.py @ 5:2436a8807ad1 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/2d_feature_extraction/ commit c045f067a57e8308308cf6329060c7ccd3fc372f

--- a/2d_feature_extraction.py	Fri Nov 10 14:23:12 2023 +0000
+++ b/2d_feature_extraction.py	Thu Apr 04 15:23:23 2024 +0000
@@ -8,119 +8,120 @@
 import skimage.morphology
 import skimage.segmentation
 
-# TODO make importable by python script
 
-parser = argparse.ArgumentParser(description='Extract Features 2D')
+if __name__ == '__main__':
+
+    parser = argparse.ArgumentParser(description='Extract image features')
 
-# TODO create factory for boilerplate code
-features = parser.add_argument_group('compute features')
-features.add_argument('--all', dest='all_features', action='store_true')
-features.add_argument('--label', dest='add_label', action='store_true')
-features.add_argument('--patches', dest='add_roi_patches', action='store_true')
-features.add_argument('--max_intensity', dest='max_intensity', action='store_true')
-features.add_argument('--mean_intensity', dest='mean_intensity', action='store_true')
-features.add_argument('--min_intensity', dest='min_intensity', action='store_true')
-features.add_argument('--moments_hu', dest='moments_hu', action='store_true')
-features.add_argument('--centroid', dest='centroid', action='store_true')
-features.add_argument('--bbox', dest='bbox', action='store_true')
-features.add_argument('--area', dest='area', action='store_true')
-features.add_argument('--filled_area', dest='filled_area', action='store_true')
-features.add_argument('--convex_area', dest='convex_area', action='store_true')
-features.add_argument('--perimeter', dest='perimeter', action='store_true')
-features.add_argument('--extent', dest='extent', action='store_true')
-features.add_argument('--eccentricity', dest='eccentricity', action='store_true')
-features.add_argument('--equivalent_diameter', dest='equivalent_diameter', action='store_true')
-features.add_argument('--euler_number', dest='euler_number', action='store_true')
-features.add_argument('--inertia_tensor_eigvals', dest='inertia_tensor_eigvals', action='store_true')
-features.add_argument('--major_axis_length', dest='major_axis_length', action='store_true')
-features.add_argument('--minor_axis_length', dest='minor_axis_length', action='store_true')
-features.add_argument('--orientation', dest='orientation', action='store_true')
-features.add_argument('--solidity', dest='solidity', action='store_true')
-features.add_argument('--moments', dest='moments', action='store_true')
-features.add_argument('--convexity', dest='convexity', action='store_true')
+    # TODO create factory for boilerplate code
+    features = parser.add_argument_group('compute features')
+    features.add_argument('--all', dest='all_features', action='store_true')
+    features.add_argument('--label', dest='add_label', action='store_true')
+    features.add_argument('--patches', dest='add_roi_patches', action='store_true')
+    features.add_argument('--max_intensity', dest='max_intensity', action='store_true')
+    features.add_argument('--mean_intensity', dest='mean_intensity', action='store_true')
+    features.add_argument('--min_intensity', dest='min_intensity', action='store_true')
+    features.add_argument('--moments_hu', dest='moments_hu', action='store_true')
+    features.add_argument('--centroid', dest='centroid', action='store_true')
+    features.add_argument('--bbox', dest='bbox', action='store_true')
+    features.add_argument('--area', dest='area', action='store_true')
+    features.add_argument('--filled_area', dest='filled_area', action='store_true')
+    features.add_argument('--convex_area', dest='convex_area', action='store_true')
+    features.add_argument('--perimeter', dest='perimeter', action='store_true')
+    features.add_argument('--extent', dest='extent', action='store_true')
+    features.add_argument('--eccentricity', dest='eccentricity', action='store_true')
+    features.add_argument('--equivalent_diameter', dest='equivalent_diameter', action='store_true')
+    features.add_argument('--euler_number', dest='euler_number', action='store_true')
+    features.add_argument('--inertia_tensor_eigvals', dest='inertia_tensor_eigvals', action='store_true')
+    features.add_argument('--major_axis_length', dest='major_axis_length', action='store_true')
+    features.add_argument('--minor_axis_length', dest='minor_axis_length', action='store_true')
+    features.add_argument('--orientation', dest='orientation', action='store_true')
+    features.add_argument('--solidity', dest='solidity', action='store_true')
+    features.add_argument('--moments', dest='moments', action='store_true')
+    features.add_argument('--convexity', dest='convexity', action='store_true')
 
-parser.add_argument('--label_file_binary', dest='label_file_binary', action='store_true')
+    parser.add_argument('--label_file_binary', dest='label_file_binary', action='store_true')
 
-parser.add_argument('--raw', dest='raw_file', type=argparse.FileType('r'),
-                    help='Original input file', required=False)
-parser.add_argument('label_file', type=argparse.FileType('r'),
-                    help='Label input file')
-parser.add_argument('output_file', type=argparse.FileType('w'),
-                    help='Tabular output file')
-args = parser.parse_args()
+    parser.add_argument('--raw', dest='raw_file', type=argparse.FileType('r'),
+                        help='Original input file', required=False)
+    parser.add_argument('label_file', type=argparse.FileType('r'),
+                        help='Label input file')
+    parser.add_argument('output_file', type=argparse.FileType('w'),
+                        help='Tabular output file')
+    args = parser.parse_args()
 
-label_file_binary = args.label_file_binary
-label_file = args.label_file.name
-out_file = args.output_file.name
-add_patch = args.add_roi_patches
+    label_file_binary = args.label_file_binary
+    label_file = args.label_file.name
+    out_file = args.output_file.name
+    add_patch = args.add_roi_patches
 
-raw_image = None
-if args.raw_file is not None:
-    raw_image = skimage.io.imread(args.raw_file.name)
+    raw_image = None
+    if args.raw_file is not None:
+        raw_image = skimage.io.imread(args.raw_file.name)
 
-raw_label_image = skimage.io.imread(label_file)
+    raw_label_image = skimage.io.imread(label_file)
 
-df = pd.DataFrame()
-if label_file_binary:
-    raw_label_image = skimage.measure.label(raw_label_image)
-regions = skimage.measure.regionprops(raw_label_image, intensity_image=raw_image)
+    df = pd.DataFrame()
+    if label_file_binary:
+        raw_label_image = skimage.measure.label(raw_label_image)
+    regions = skimage.measure.regionprops(raw_label_image, intensity_image=raw_image)
 
-df['it'] = np.arange(len(regions))
+    df['it'] = np.arange(len(regions))
 
-if add_patch:
-    df['image'] = df['it'].map(lambda ait: regions[ait].image.astype(np.float).tolist())
-    df['intensity_image'] = df['it'].map(lambda ait: regions[ait].intensity_image.astype(np.float).tolist())
+    if add_patch:
+        df['image'] = df['it'].map(lambda ait: regions[ait].image.astype(np.float).tolist())
+        df['intensity_image'] = df['it'].map(lambda ait: regions[ait].intensity_image.astype(np.float).tolist())
 
-# TODO no matrix features, but split in own rows?
-if args.add_label or args.all_features:
-    df['label'] = df['it'].map(lambda ait: regions[ait].label)
+    # TODO no matrix features, but split in own rows?
+    if args.add_label or args.all_features:
+        df['label'] = df['it'].map(lambda ait: regions[ait].label)
 
-if raw_image is not None:
-    if args.max_intensity or args.all_features:
-        df['max_intensity'] = df['it'].map(lambda ait: regions[ait].max_intensity)
-    if args.mean_intensity or args.all_features:
-        df['mean_intensity'] = df['it'].map(lambda ait: regions[ait].mean_intensity)
-    if args.min_intensity or args.all_features:
-        df['min_intensity'] = df['it'].map(lambda ait: regions[ait].min_intensity)
-    if args.moments_hu or args.all_features:
-        df['moments_hu'] = df['it'].map(lambda ait: regions[ait].moments_hu)
+    if raw_image is not None:
+        if args.max_intensity or args.all_features:
+            df['max_intensity'] = df['it'].map(lambda ait: regions[ait].max_intensity)
+        if args.mean_intensity or args.all_features:
+            df['mean_intensity'] = df['it'].map(lambda ait: regions[ait].mean_intensity)
+        if args.min_intensity or args.all_features:
+            df['min_intensity'] = df['it'].map(lambda ait: regions[ait].min_intensity)
+        if args.moments_hu or args.all_features:
+            df['moments_hu'] = df['it'].map(lambda ait: regions[ait].moments_hu)
 
-if args.centroid or args.all_features:
-    df['centroid'] = df['it'].map(lambda ait: regions[ait].centroid)
-if args.bbox or args.all_features:
-    df['bbox'] = df['it'].map(lambda ait: regions[ait].bbox)
-if args.area or args.all_features:
-    df['area'] = df['it'].map(lambda ait: regions[ait].area)
-if args.filled_area or args.all_features:
-    df['filled_area'] = df['it'].map(lambda ait: regions[ait].filled_area)
-if args.convex_area or args.all_features:
-    df['convex_area'] = df['it'].map(lambda ait: regions[ait].convex_area)
-if args.perimeter or args.all_features:
-    df['perimeter'] = df['it'].map(lambda ait: regions[ait].perimeter)
-if args.extent or args.all_features:
-    df['extent'] = df['it'].map(lambda ait: regions[ait].extent)
-if args.eccentricity or args.all_features:
-    df['eccentricity'] = df['it'].map(lambda ait: regions[ait].eccentricity)
-if args.equivalent_diameter or args.all_features:
-    df['equivalent_diameter'] = df['it'].map(lambda ait: regions[ait].equivalent_diameter)
-if args.euler_number or args.all_features:
-    df['euler_number'] = df['it'].map(lambda ait: regions[ait].euler_number)
-if args.inertia_tensor_eigvals or args.all_features:
-    df['inertia_tensor_eigvals'] = df['it'].map(lambda ait: regions[ait].inertia_tensor_eigvals)
-if args.major_axis_length or args.all_features:
-    df['major_axis_length'] = df['it'].map(lambda ait: regions[ait].major_axis_length)
-if args.minor_axis_length or args.all_features:
-    df['minor_axis_length'] = df['it'].map(lambda ait: regions[ait].minor_axis_length)
-if args.orientation or args.all_features:
-    df['orientation'] = df['it'].map(lambda ait: regions[ait].orientation)
-if args.solidity or args.all_features:
-    df['solidity'] = df['it'].map(lambda ait: regions[ait].solidity)
-if args.moments or args.all_features:
-    df['moments'] = df['it'].map(lambda ait: regions[ait].moments)
-if args.convexity or args.all_features:
-    perimeter = df['it'].map(lambda ait: regions[ait].perimeter)
-    area = df['it'].map(lambda ait: regions[ait].area)
-    df['convexity'] = area / (perimeter * perimeter)
+    if args.centroid or args.all_features:
+        df['centroid'] = df['it'].map(lambda ait: regions[ait].centroid)
+    if args.bbox or args.all_features:
+        df['bbox'] = df['it'].map(lambda ait: regions[ait].bbox)
+    if args.area or args.all_features:
+        df['area'] = df['it'].map(lambda ait: regions[ait].area)
+    if args.filled_area or args.all_features:
+        df['filled_area'] = df['it'].map(lambda ait: regions[ait].filled_area)
+    if args.convex_area or args.all_features:
+        df['convex_area'] = df['it'].map(lambda ait: regions[ait].convex_area)
+    if args.perimeter or args.all_features:
+        df['perimeter'] = df['it'].map(lambda ait: regions[ait].perimeter)
+    if args.extent or args.all_features:
+        df['extent'] = df['it'].map(lambda ait: regions[ait].extent)
+    if args.eccentricity or args.all_features:
+        df['eccentricity'] = df['it'].map(lambda ait: regions[ait].eccentricity)
+    if args.equivalent_diameter or args.all_features:
+        df['equivalent_diameter'] = df['it'].map(lambda ait: regions[ait].equivalent_diameter)
+    if args.euler_number or args.all_features:
+        df['euler_number'] = df['it'].map(lambda ait: regions[ait].euler_number)
+    if args.inertia_tensor_eigvals or args.all_features:
+        df['inertia_tensor_eigvals'] = df['it'].map(lambda ait: regions[ait].inertia_tensor_eigvals)
+    if args.major_axis_length or args.all_features:
+        df['major_axis_length'] = df['it'].map(lambda ait: regions[ait].major_axis_length)
+    if args.minor_axis_length or args.all_features:
+        df['minor_axis_length'] = df['it'].map(lambda ait: regions[ait].minor_axis_length)
+    if args.orientation or args.all_features:
+        df['orientation'] = df['it'].map(lambda ait: regions[ait].orientation)
+    if args.solidity or args.all_features:
+        df['solidity'] = df['it'].map(lambda ait: regions[ait].solidity)
+    if args.moments or args.all_features:
+        df['moments'] = df['it'].map(lambda ait: regions[ait].moments)
+    if args.convexity or args.all_features:
+        perimeter = df['it'].map(lambda ait: regions[ait].perimeter)
+        area = df['it'].map(lambda ait: regions[ait].area)
+        df['convexity'] = area / (perimeter * perimeter)
 
-del df['it']
-df.to_csv(out_file, sep='\t', line_terminator='\n', index=False)
+    del df['it']
+    df.to_csv(out_file, sep='\t', line_terminator='\n', index=False)