1# Copyright 2021 Huawei Technologies Co., Ltd 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15""" 16Testing GaussianBlur Python API 17""" 18import cv2 19 20import mindspore.dataset as ds 21import mindspore.dataset.vision.c_transforms as c_vision 22 23from mindspore import log as logger 24from util import visualize_image, diff_mse 25 26DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"] 27SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json" 28IMAGE_FILE = "../data/dataset/apple.jpg" 29 30 31def test_gaussian_blur_pipeline(plot=False): 32 """ 33 Test GaussianBlur of c_transforms 34 """ 35 logger.info("test_gaussian_blur_pipeline") 36 37 # First dataset 38 dataset1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False) 39 decode_op = c_vision.Decode() 40 gaussian_blur_op = c_vision.GaussianBlur(3, 3) 41 dataset1 = dataset1.map(operations=decode_op, input_columns=["image"]) 42 dataset1 = dataset1.map(operations=gaussian_blur_op, input_columns=["image"]) 43 44 # Second dataset 45 dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 46 dataset2 = dataset2.map(operations=decode_op, input_columns=["image"]) 47 48 num_iter = 0 49 for data1, data2 in zip(dataset1.create_dict_iterator(num_epochs=1, output_numpy=True), 50 dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)): 51 if num_iter > 0: 52 break 53 gaussian_blur_ms = data1["image"] 54 original = data2["image"] 55 gaussian_blur_cv = cv2.GaussianBlur(original, (3, 3), 3) 56 mse = diff_mse(gaussian_blur_ms, gaussian_blur_cv) 57 logger.info("gaussian_blur_{}, mse: {}".format(num_iter + 1, mse)) 58 assert mse == 0 59 num_iter += 1 60 if plot: 61 visualize_image(original, gaussian_blur_ms, mse, gaussian_blur_cv) 62 63 64def test_gaussian_blur_eager(): 65 """ 66 Test GaussianBlur with eager mode 67 """ 68 logger.info("test_gaussian_blur_eager") 69 img = cv2.imread(IMAGE_FILE) 70 71 img_ms = c_vision.GaussianBlur((3, 5), (3.5, 3.5))(img) 72 img_cv = cv2.GaussianBlur(img, (3, 5), 3.5, 3.5) 73 mse = diff_mse(img_ms, img_cv) 74 assert mse == 0 75 76 77def test_gaussian_blur_exception(): 78 """ 79 Test GaussianBlur with invalid parameters 80 """ 81 logger.info("test_gaussian_blur_exception") 82 try: 83 _ = c_vision.GaussianBlur([2, 2]) 84 except ValueError as e: 85 logger.info("Got an exception in GaussianBlur: {}".format(str(e))) 86 assert "not an odd value" in str(e) 87 try: 88 _ = c_vision.GaussianBlur(3.0, [3, 3]) 89 except TypeError as e: 90 logger.info("Got an exception in GaussianBlur: {}".format(str(e))) 91 assert "not of type [<class 'int'>, <class 'list'>, <class 'tuple'>]" in str(e) 92 try: 93 _ = c_vision.GaussianBlur(3, -3) 94 except ValueError as e: 95 logger.info("Got an exception in GaussianBlur: {}".format(str(e))) 96 assert "not within the required interval" in str(e) 97 try: 98 _ = c_vision.GaussianBlur(3, [3, 3, 3]) 99 except TypeError as e: 100 logger.info("Got an exception in GaussianBlur: {}".format(str(e))) 101 assert "should be a single number or a list/tuple of length 2" in str(e) 102 103 104if __name__ == "__main__": 105 test_gaussian_blur_pipeline(plot=False) 106 test_gaussian_blur_eager() 107 test_gaussian_blur_exception() 108
