INNER CODE UNIT · Python
get_all_train_faces
MITDeepLearning/introtodeeplearning · mitdeeplearning/lab2.py:108
def get_all_train_faces(self):
return self.images[self.pos_train_inds]
def get_test_faces(channels_last=True):
cwd = os.path.dirname(__file__)
images = {"LF": [], "LM": [], "DF": [], "DM": []}
for key in images.keys():
files = glob.glob(os.path.join(cwd, "data", "faces", key, "*.png"))
for file in sorted(files):
image = cv2.resize(cv2.imread(file), (64, 64))[:, :, ::-1] / 255.0
if not channels_last:
image = np.transpose(image, (2, 0, 1))
images[key].append(image)
return images["LF"], images["LM"], images["DF"], images["DM"]