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src/x/b/xbob.example.faceverify-1.0.0/xbob/example/faceverify/dct_ubm.py xbob.example.faceverify(Download)
# create a DCT block extractor model dct_extractor = bob.ip.DCTFeatures(DCT_BLOCK_SIZE, DCT_BLOCK_SIZE, DCT_BLOCK_OVERLAP, DCT_BLOCK_OVERLAP, NUMBER_OF_DCT_COMPONENTS) def extract_feature(image): """Extracts the DCT features for the given image""" # extract DCT blocks return dct_extractor(image)
src/a/n/antispoofing.verification.gmm-1.0.2/antispoofing/verification/features/dct.py antispoofing.verification.gmm(Download)
# Initializes cropper and destination array DCTF = bob.ip.DCTFeatures(A_BLOCK_H, A_BLOCK_W, A_OVERLAP_H, A_OVERLAP_W, real_DCT_coef) # Calls the preprocessing algorithm dct_blocks = DCTF(blocks)
src/f/a/facereclib-1.2.1/facereclib/features/DCT.py facereclib(Download)
def __call__(self, image): """Computes and returns DCT blocks for the given input image""" # Initializes cropper and destination array extractor = bob.ip.DCTFeatures(self.m_block_size[0], self.m_block_size[1], self.m_block_overlap[0], self.m_block_overlap[1], self.m_number_of_dct_coefficients, self.norm_block, self.norm_dct) # Computes DCT features return extractor(image)
src/f/a/facereclib-HEAD/facereclib/features/DCT.py facereclib(Download)
def __call__(self, image): """Computes and returns DCT blocks for the given input image""" # Initializes cropper and destination array extractor = bob.ip.DCTFeatures(self.m_block_size[0], self.m_block_size[1], self.m_block_overlap[0], self.m_block_overlap[1], self.m_number_of_dct_coefficients, self.norm_block, self.norm_dct) # Computes DCT features return extractor(image)
src/m/a/maskattack.study-1.0.0/maskattack/study/analyze/isv.py maskattack.study(Download)
if not os.path.exists(file_name): print 'Extracting/loading DCT features for mask #%d..' %mask extractor = bob.ip.DCTFeatures(12,12,11,11,dct_size,True,True) train_dct = create_full_dataset(inputdir,ftdir,train,extractor,True) create_full_dataset(inputdir,ftdir,dev_enrol,extractor)