# Copyright 2021 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """ Testing Crop op in DE """ import cv2 import mindspore.dataset as ds import mindspore.dataset.vision.c_transforms as c_vision from mindspore import log as logger from util import visualize_image, diff_mse DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"] SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json" IMAGE_FILE = "../data/dataset/apple.jpg" def test_crop_pipeline(plot=False): """ Test Crop of c_transforms """ logger.info("test_crop_pipeline") # First dataset dataset1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False) decode_op = c_vision.Decode() crop_op = c_vision.Crop((0, 0), (20, 25)) dataset1 = dataset1.map(operations=decode_op, input_columns=["image"]) dataset1 = dataset1.map(operations=crop_op, input_columns=["image"]) # Second dataset dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) dataset2 = dataset2.map(operations=decode_op, input_columns=["image"]) num_iter = 0 for data1, data2 in zip(dataset1.create_dict_iterator(num_epochs=1, output_numpy=True), dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)): if num_iter > 0: break crop_ms = data1["image"] original = data2["image"] crop_expect = original[0:20, 0:25] mse = diff_mse(crop_ms, crop_expect) logger.info("crop_{}, mse: {}".format(num_iter + 1, mse)) assert mse == 0 num_iter += 1 if plot: visualize_image(original, crop_ms, mse, crop_expect) def test_crop_eager(): """ Test Crop with eager mode """ logger.info("test_crop_eager") img = cv2.imread(IMAGE_FILE) img_ms = c_vision.Crop((20, 50), (30, 50))(img) img_expect = img[20:50, 50:100] mse = diff_mse(img_ms, img_expect) assert mse == 0 def test_crop_exception(): """ Test Crop with invalid parameters """ logger.info("test_crop_exception") try: _ = c_vision.Crop([-10, 0], [20]) except ValueError as e: logger.info("Got an exception in Crop: {}".format(str(e))) assert "not within the required interval of [0, 2147483647]" in str(e) try: _ = c_vision.Crop([0, 5.2], [10, 10]) except TypeError as e: logger.info("Got an exception in Crop: {}".format(str(e))) assert "not of type []" in str(e) try: _ = c_vision.Crop([0], [28]) except TypeError as e: logger.info("Got an exception in Crop: {}".format(str(e))) assert "Coordinates should be a list/tuple (y, x) of length 2." in str(e) try: _ = c_vision.Crop((0, 0), -1) except ValueError as e: logger.info("Got an exception in Crop: {}".format(str(e))) assert "not within the required interval of [1, 16777216]" in str(e) try: _ = c_vision.Crop((0, 0), (10.5, 15)) except TypeError as e: logger.info("Got an exception in Crop: {}".format(str(e))) assert "not of type []" in str(e) try: _ = c_vision.Crop((0, 0), (0, 10, 20)) except TypeError as e: logger.info("Got an exception in Crop: {}".format(str(e))) assert "Size should be a single integer or a list/tuple (h, w) of length 2." in str(e) if __name__ == "__main__": test_crop_pipeline(plot=False) test_crop_eager() test_crop_exception()