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)