MODEL_FILE_NAME = sys.argv[1] actFunc = sys.argv[2] npzSaveFile = sys.argv[3] img_hndlr = ImageHandler((64, 64)) path = "dataset" if not (os.path.exists(path + "/dark/") and os.path.exists(path + "/true/")): img_hndlr.create_dataset(path) X = img_hndlr.load_images(path + "/dark/") Y = img_hndlr.load_images(path + "/true/") X = img_hndlr.preprocess_images(X) Y = img_hndlr.preprocess_images(Y) print("XY shapes", X.shape, Y.shape) print("python msrnet.py") m = None xx = Input( (64, 64, 3)) # tf.constant(np.ndarray((?,100,100,3),dtype=np.float32)) # nnOut,loss=nn(xx) nnOut = nn(xx, actFunc) m = Model(xx, nnOut) m.compile(optimizer="adam", loss='mean_squared_error', metrics=['mean_squared_error'])