I had success by replacing the get_mask function with: from keras.models import load_model model = load_model('models/transpose_seg/deconv_bnoptimized

I had success by replacing the get_mask function with: from keras.models import load_model model = load_model('models/transpose_seg/deconv_bnoptimized_munet.h5', compile=False) def get_mask(frame): # Preprocess frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) simg = cv2.resize(frame, (128, 128), interpolation=cv2.INTER_AREA) simg = simg.reshape((1, 128, 128, 3)) / 255.0 # Predict out = model.predict(simg) # Postprocess msk = out.reshape((128, 128, 1)) mask = cv2.resize(msk, (frame.shape[1], frame.shape[0])) return mask The model file I got from: https://github.com/anilsathyan7/Portrait-Segmentation https://github.com/anilsathyan7/Portrait-Segmentation