Chris Oswald commited on
Commit
7ed1b1f
1 Parent(s): 642a1ea
Files changed (1) hide show
  1. SPIDER.py +9 -8
SPIDER.py CHANGED
@@ -44,15 +44,16 @@ 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, int]
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  ) -> np.ndarray:
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  """Aligns dimensions of image to be (height, width, channels) and resizes
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- images to values specified in resize_shape."""
 
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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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  # Resize image
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- image = skimage.transform.resize(image, resize_shape)
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  # Rescale to UInt8 type
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  image = skimage.img_as_ubyte(image)
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  return image
@@ -63,7 +64,7 @@ N_PATIENTS = 218
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  MIN_IVD = 0
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  MAX_IVD = 9
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  DEFAULT_SCAN_TYPES = ['t1', 't2', 't2_SPACE']
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- DEFAULT_RESIZE = (512, 512, 30)
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  _CITATION = """\
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  @misc{vandergraaf2023lumbar,
@@ -193,8 +194,8 @@ 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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- "image": datasets.Image("uint8"),
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- "mask": datasets.Image("uint8"),
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  # "image": datasets.Array3D(shape=self.config.resize_shape, dtype='uint8'),
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  # "mask": datasets.Array3D(shape=self.config.resize_shape, dtype='uint8'),
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  "image_path": datasets.Value("string"),
@@ -519,8 +520,8 @@ 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':datasets.Image().encode_example(image_array_standardized),
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- 'mask':datasets.Image().encode_example(mask_array_standardized),
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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) and resizes
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+ images to values specified in resize_shape (note that original channels
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+ are preserved)."""
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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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  # Resize image
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+ image = skimage.transform.resize(image, resize_shape) # Preserves original channels
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  # Rescale to UInt8 type
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  image = skimage.img_as_ubyte(image)
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  return image
 
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  MIN_IVD = 0
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  MAX_IVD = 9
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  DEFAULT_SCAN_TYPES = ['t1', 't2', 't2_SPACE']
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+ DEFAULT_RESIZE = (512, 512)
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  _CITATION = """\
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  @misc{vandergraaf2023lumbar,
 
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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": datasets.Array3D(dtype='uint8'),
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+ "mask": datasets.Array3D(dtype='uint8'),
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  # "image": datasets.Array3D(shape=self.config.resize_shape, dtype='uint8'),
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  # "mask": datasets.Array3D(shape=self.config.resize_shape, dtype='uint8'),
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  "image_path": datasets.Value("string"),
 
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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_array':image_array_standardized,
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+ 'mask_array':mask_array_standardized,
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  'image_path':image_path,
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  'mask_path':mask_path,
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  'metadata':image_overview,