text_plain_output_1.png
for y in range(0, h - INPUT_DIM + 1, LABEL_SIZE):
    for x in range(0, w - INPUT_DIM + 1, LABEL_SIZE):
        crop = scaled[y:y + INPUT_DIM, x:x + INPUT_DIM].astype('float32')
        P = model.predict(np.expand_dims(crop, axis=0))
        P = P.reshape((LABEL_SIZE, LABEL_SIZE, 3))
        output[y + PAD:y + PAD + LABEL_SIZE, x + PAD:x + PAD + LABEL_SIZE] = P