def extract_patches(volume, patch_shape, extraction_step):
patches = sk_extract_patches(volume,
patch_shape=patch_shape,
extraction_step=extraction_step)
ndim = len(volume.shape)
npatches = np.prod(patches.shape[:ndim])
return patches.reshape((npatches, ) + patch_shape)
def extract_patches(img, patch_shape, extraction_step):
from sklearn.feature_extraction.image import extract_patches as sk_extract_patches
patches = sk_extract_patches(img,
patch_shape=patch_shape,
extraction_step=extraction_step)
ndim = img.ndim
npatches = np.prod(patches.shape[:ndim])
return patches.reshape((npatches, ) + patch_shape)
def extract_patches(dimension, volume, patch_shape, extraction_step):
actual_patch_shape = patch_shape
actual_extraction_step = extraction_step
# todo: need to check!!!
if dimension == 2:
if len(actual_patch_shape) == 3:
actual_patch_shape = actual_patch_shape[:1] + (
1, ) + actual_patch_shape[1:]
actual_extraction_step = actual_extraction_step[:1] + (
1, ) + actual_extraction_step[1:]
else:
actual_patch_shape = (1, ) + actual_patch_shape
actual_extraction_step = (1, ) + actual_extraction_step
patches = sk_extract_patches(volume,
patch_shape=actual_patch_shape,
extraction_step=actual_extraction_step)
ndim = len(volume.shape)
npatches = np.prod(patches.shape[:ndim])
return patches.reshape((npatches, ) + patch_shape)
def extract_patches(dimension, volume, patch_shape, extraction_step):
actual_patch_shape = patch_shape
actual_extraction_step = extraction_step
if dimension == 2:
if len(actual_patch_shape) == 3:
actual_patch_shape = actual_patch_shape[:1] + (
1, ) + actual_patch_shape[1:]
actual_extraction_step = actual_extraction_step[:1] + (
1, ) + actual_extraction_step[1:]
else:
actual_patch_shape = (1, ) + actual_patch_shape
actual_extraction_step = (1, ) + actual_extraction_step
patches = sk_extract_patches(volume,
patch_shape=actual_patch_shape,
extraction_step=actual_extraction_step)
ndim = len(volume.shape)
npatches = np.prod(patches.shape[:ndim])
print(np.shape(patches))
#print(np.shape(patches.reshape([-1] + list(patch_shape))))
return patches.reshape((npatches, ) + patch_shape)
