Chris Oswald commited on
Commit
76cb606
1 Parent(s): ba3659a
Files changed (1) hide show
  1. SPIDER.py +10 -14
SPIDER.py CHANGED
@@ -170,8 +170,8 @@ class SPIDER(datasets.GeneratorBasedBuilder):
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  features = datasets.Features({
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  "patient_id": datasets.Value("string"),
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  "scan_type": datasets.Value("string"),
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- "raw_image": datasets.Image(decode=False),
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- "raw_mask": datasets.Image(decode=False),
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  "image_array": datasets.Array3D(shape=image_size, dtype='float64'),
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  "mask_array": datasets.Array3D(shape=image_size, dtype='float64'),
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  "metadata": {
@@ -479,8 +479,8 @@ class SPIDER(datasets.GeneratorBasedBuilder):
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  image_path = os.path.join(paths_dict['images'], 'images', example)
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  image = sitk.ReadImage(image_path)
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- # Rescale image intensities to [0, 255] and cast as UInt8 type
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- image = sitk.Cast(sitk.RescaleIntensity(image), sitk.sitkUInt8)
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  # Convert .mha image to original size numeric array
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  image_array_original = sitk.GetArrayFromImage(image)
@@ -491,15 +491,14 @@ class SPIDER(datasets.GeneratorBasedBuilder):
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  resize_shape,
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  )
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- # Create PIL image object of original image
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- # PIL_original_image = PIL.Image.fromarray(image_array_original)
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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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  mask = sitk.ReadImage(mask_path)
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- # Rescale mask intensities to [0, 255] and cast as UInt8 type
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- mask = sitk.Cast(sitk.RescaleIntensity(mask), sitk.sitkUInt8)
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  # Convert .mha mask to original size numeric array
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  mask_array_original = sitk.GetArrayFromImage(mask)
@@ -510,9 +509,6 @@ class SPIDER(datasets.GeneratorBasedBuilder):
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  resize_shape,
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  )
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- # Create PIL image object of original mask
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- # PIL_original_mask = PIL.Image.fromarray(mask_array_original)
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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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@@ -523,8 +519,8 @@ 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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- 'raw_image':image_array_original,
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- 'raw_mask':mask_array_original,
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  'image_array':image_array_standardized,
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  'mask_array':mask_array_standardized,
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  'metadata':image_overview,
 
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  features = datasets.Features({
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  "patient_id": datasets.Value("string"),
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  "scan_type": datasets.Value("string"),
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+ "image_path": datasets.Value("string"),
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+ "mask_path": datasets.Value("string"),
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  "image_array": datasets.Array3D(shape=image_size, dtype='float64'),
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  "mask_array": datasets.Array3D(shape=image_size, dtype='float64'),
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  "metadata": {
 
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  image_path = os.path.join(paths_dict['images'], 'images', example)
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  image = sitk.ReadImage(image_path)
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+ # # Rescale image intensities to [0, 255] and cast as UInt8 type
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+ # image = sitk.Cast(sitk.RescaleIntensity(image), sitk.sitkUInt8)
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  # Convert .mha image to original size numeric array
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  image_array_original = sitk.GetArrayFromImage(image)
 
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  resize_shape,
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  )
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+ # NOTE: since the original array shape is not standardized, cannot return in dataset
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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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  mask = sitk.ReadImage(mask_path)
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+ # # Rescale mask intensities to [0, 255] and cast as UInt8 type
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+ # mask = sitk.Cast(sitk.RescaleIntensity(mask), sitk.sitkUInt8)
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  # Convert .mha mask to original size numeric array
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  mask_array_original = sitk.GetArrayFromImage(mask)
 
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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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  return_dict = {
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  'patient_id':patient_id,
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  'scan_type':scan_type,
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+ 'image_path':image_path,
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+ 'mask_path':mask_path,
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  'image_array':image_array_standardized,
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  'mask_array':mask_array_standardized,
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  'metadata':image_overview,