def test_random_choice_exception_random_crop_badinput(): """ Test RandomChoice: hit error in RandomCrop with greater crop size, expected to raise error """ logger.info("test_random_choice_exception_random_crop_badinput") # define map operations # note: crop size[5000, 5000] > image size[4032, 2268] transforms_list = [py_vision.RandomCrop(5000)] transforms = [ py_vision.Decode(), py_vision.RandomChoice(transforms_list), py_vision.ToTensor() ] transform = py_vision.ComposeOp(transforms) # Generate dataset data = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) data = data.map(input_columns=["image"], operations=transform()) try: _ = data.create_dict_iterator().get_next() except RuntimeError as e: logger.info("Got an exception in DE: {}".format(str(e))) assert "Crop size" in str(e)
def test_random_choice_comp(plot=False): """ Test RandomChoice and compare with single CenterCrop results """ logger.info("test_random_choice_comp") # define map operations transforms_list = [py_vision.CenterCrop(64)] transforms1 = [ py_vision.Decode(), py_vision.RandomChoice(transforms_list), py_vision.ToTensor() ] transform1 = py_vision.ComposeOp(transforms1) transforms2 = [ py_vision.Decode(), py_vision.CenterCrop(64), py_vision.ToTensor() ] transform2 = py_vision.ComposeOp(transforms2) # First dataset data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) data1 = data1.map(input_columns=["image"], operations=transform1()) # Second dataset data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) data2 = data2.map(input_columns=["image"], operations=transform2()) image_choice = [] image_original = [] for item1, item2 in zip(data1.create_dict_iterator(), data2.create_dict_iterator()): image1 = (item1["image"].transpose(1, 2, 0) * 255).astype(np.uint8) image2 = (item2["image"].transpose(1, 2, 0) * 255).astype(np.uint8) image_choice.append(image1) image_original.append(image2) mse = diff_mse(image1, image2) assert mse == 0 if plot: visualize_list(image_original, image_choice)