Chris Oswald
commited on
Commit
·
da94d71
1
Parent(s):
b4f24a3
converted to sequence of images
Browse files
SPIDER.py
CHANGED
@@ -66,11 +66,11 @@ def subset_file_list(all_files: List[str], subset_ids: Set[int]):
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def standardize_3D_image(
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image: np.ndarray,
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-
resize_shape: Tuple[int, int
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) -> np.ndarray:
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"""Aligns dimensions of image to be (height, width, channels); resizes
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images to values specified in resize_shape; and rescales
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to Uint8."""
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# Align height, width, channel dims
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if image.shape[0] < image.shape[2]:
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image = np.transpose(image, axes=[1, 2, 0])
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@@ -519,6 +519,16 @@ class SPIDER(datasets.GeneratorBasedBuilder):
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image_array_original,
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resize_shape,
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)
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# Load .mha mask file
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mask_path = os.path.join(paths_dict['masks'], 'masks', example)
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@@ -537,6 +547,16 @@ class SPIDER(datasets.GeneratorBasedBuilder):
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resize_shape,
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)
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# Extract overview data corresponding to image
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image_overview = overview_dict[scan_id]
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@@ -547,8 +567,8 @@ class SPIDER(datasets.GeneratorBasedBuilder):
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return_dict = {
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'patient_id':patient_id,
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'scan_type':scan_type,
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'image':
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'mask':
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'image_path':image_path,
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'mask_path':mask_path,
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'metadata':image_overview,
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def standardize_3D_image(
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image: np.ndarray,
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+
resize_shape: Tuple[int, int],
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) -> np.ndarray:
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"""Aligns dimensions of image to be (height, width, channels); resizes
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+
images to height/width values specified in resize_shape; and rescales
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+
pixel values to Uint8."""
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# Align height, width, channel dims
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if image.shape[0] < image.shape[2]:
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image = np.transpose(image, axes=[1, 2, 0])
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image_array_original,
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resize_shape,
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)
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+
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+
# Split image array into sequence of 2D images
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split_len = image_array_standardized.shape[-1]
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images_seq = [
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np.squeeze(arr) for arr in np.split(
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image_array_standardized,
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split_len,
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axis=-1,
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)
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]
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# Load .mha mask file
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mask_path = os.path.join(paths_dict['masks'], 'masks', example)
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resize_shape,
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)
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+
# Split mask array into sequence of 2D images
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split_len = mask_array_standardized.shape[-1]
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masks_seq = [
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np.squeeze(arr) for arr in np.split(
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mask_array_standardized,
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split_len,
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axis=-1,
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)
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]
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# Extract overview data corresponding to image
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image_overview = overview_dict[scan_id]
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return_dict = {
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'patient_id':patient_id,
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'scan_type':scan_type,
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'image':images_seq,
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'mask':masks_seq,
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'image_path':image_path,
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'mask_path':mask_path,
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'metadata':image_overview,
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