diff morphological_operations.py @ 0:f10112b317a1 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/morphological_operations commit c6d2a4fb19b54c804029ae3d52eb9fb2619e4265

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/morphological_operations.py	Fri Mar 08 11:00:41 2024 +0000
@@ -0,0 +1,93 @@
+import argparse
+
+import numpy as np
+import scipy.ndimage as ndi
+import skimage.io
+import skimage.morphology as morph
+
+
+def create_selem(args):
+    """
+    Creates structuring element based on commandline arguments.
+    """
+    assert args.selem_shape in (
+        'square',
+        'disk',
+    )
+
+    if args.selem_shape == 'square':
+        return np.ones((args.selem_size, args.selem_size))
+
+    elif args.selem_shape == 'disk':
+        return morph.disk(args.selem_size)
+
+
+def apply_operation(args, im):
+    """
+    Applies morphological operation to a 2-D single-channel image.
+    """
+    assert im.ndim == 2
+    selem = create_selem(args)
+    values_count = len(np.unique(im))
+    if values_count <= 2:
+        im_proxy = np.zeros(im.shape, bool)
+        im_proxy[im == im.max()] = True
+        result_proxy = apply_binary_operation(args, im_proxy, selem)
+        result = np.full(im.shape, im.min(), im.dtype)
+        result[result_proxy] = im.max()
+        return result
+    else:
+        return apply_intensity_based_operation(args, im, selem)
+
+
+def apply_intensity_based_operation(args, im, selem):
+    operations = {
+        'erosion': ndi.grey_erosion,
+        'dilation': ndi.grey_dilation,
+        'opening': ndi.grey_opening,
+        'closing': ndi.grey_closing,
+    }
+    if args.operation in operations:
+        operation = operations[args.operation]
+        return operation(input=im, structure=selem)
+    else:
+        raise ValueError(f'Operation "{args.operation}" not supported for this image type ({im.dtype}).')
+
+
+def apply_binary_operation(args, im, selem):
+    operations = {
+        'erosion': ndi.binary_erosion,
+        'dilation': ndi.binary_dilation,
+        'opening': ndi.binary_opening,
+        'closing': ndi.binary_closing,
+        'fill_holes': ndi.binary_fill_holes,
+    }
+    operation = operations[args.operation]
+    return operation(input=im, structure=selem)
+
+
+if __name__ == '__main__':
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--operation', type=str)
+    parser.add_argument('--selem-shape', type=str)
+    parser.add_argument('--selem-size', type=int)
+    parser.add_argument('input', type=str)
+    parser.add_argument('output', type=str)
+    args = parser.parse_args()
+
+    im = skimage.io.imread(args.input)
+    assert im.ndim in (2, 3), 'Input image must be two-dimensional and either single-channel or multi-channel.'
+
+    if im.ndim == 2:
+        im_result = apply_operation(args, im)
+
+    else:
+        ch_result_list = []
+        for ch_idx in range(im.shape[2]):
+            ch = im[:, :, ch_idx]
+            ch_result = apply_operation(args, ch)
+            ch_result_list.append(ch_result)
+        im_result = np.dstack(ch_result_list)
+
+    skimage.io.imsave(args.output, im_result)