1# Copyright 2020 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 Resize op in DE 17""" 18import pytest 19import mindspore.dataset as ds 20import mindspore.dataset.vision.c_transforms as vision 21import mindspore.dataset.vision.py_transforms as py_vision 22from mindspore.dataset.vision.utils import Inter 23from mindspore import log as logger 24from util import visualize_list, save_and_check_md5, \ 25 config_get_set_seed, config_get_set_num_parallel_workers 26 27DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"] 28SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json" 29 30GENERATE_GOLDEN = False 31 32 33def test_resize_op(plot=False): 34 def test_resize_op_parameters(test_name, size, plot): 35 """ 36 Test resize_op 37 """ 38 logger.info("Test resize: {0}".format(test_name)) 39 data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 40 41 # define map operations 42 decode_op = vision.Decode() 43 resize_op = vision.Resize(size) 44 45 # apply map operations on images 46 data1 = data1.map(operations=decode_op, input_columns=["image"]) 47 48 data2 = data1.map(operations=resize_op, input_columns=["image"]) 49 image_original = [] 50 image_resized = [] 51 for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1, output_numpy=True), 52 data2.create_dict_iterator(num_epochs=1, output_numpy=True)): 53 image_1 = item1["image"] 54 image_2 = item2["image"] 55 image_original.append(image_1) 56 image_resized.append(image_2) 57 if plot: 58 visualize_list(image_original, image_resized) 59 60 test_resize_op_parameters("Test single int for size", 10, plot=False) 61 test_resize_op_parameters("Test tuple for size", (10, 15), plot=False) 62 63def test_resize_op_ANTIALIAS(): 64 """ 65 Test resize_op 66 """ 67 logger.info("Test resize for ANTIALIAS") 68 data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 69 70 # define map operations 71 decode_op = py_vision.Decode() 72 resize_op = py_vision.Resize(20, Inter.ANTIALIAS) 73 74 # apply map operations on images 75 data1 = data1.map(operations=[decode_op, resize_op, py_vision.ToTensor()], input_columns=["image"]) 76 77 num_iter = 0 78 for _ in data1.create_dict_iterator(num_epochs=1, output_numpy=True): 79 num_iter += 1 80 logger.info("use Resize by Inter.ANTIALIAS process {} images.".format(num_iter)) 81 82def test_resize_md5(plot=False): 83 def test_resize_md5_parameters(test_name, size, filename, seed, plot): 84 """ 85 Test Resize with md5 check 86 """ 87 logger.info("Test Resize with md5 check: {0}".format(test_name)) 88 original_seed = config_get_set_seed(seed) 89 original_num_parallel_workers = config_get_set_num_parallel_workers(1) 90 91 # Generate dataset 92 data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) 93 decode_op = vision.Decode() 94 resize_op = vision.Resize(size) 95 data1 = data1.map(operations=decode_op, input_columns=["image"]) 96 data2 = data1.map(operations=resize_op, input_columns=["image"]) 97 image_original = [] 98 image_resized = [] 99 # Compare with expected md5 from images 100 save_and_check_md5(data1, filename, generate_golden=GENERATE_GOLDEN) 101 102 for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1, output_numpy=True), 103 data2.create_dict_iterator(num_epochs=1, output_numpy=True)): 104 image_1 = item1["image"] 105 image_2 = item2["image"] 106 image_original.append(image_1) 107 image_resized.append(image_2) 108 if plot: 109 visualize_list(image_original, image_resized) 110 111 # Restore configuration 112 ds.config.set_seed(original_seed) 113 ds.config.set_num_parallel_workers(original_num_parallel_workers) 114 115 test_resize_md5_parameters("Test single int for size", 5, "resize_01_result.npz", 5, plot) 116 test_resize_md5_parameters("Test tuple for size", (5, 7), "resize_02_result.npz", 7, plot) 117 118 119def test_resize_op_invalid_input(): 120 def test_invalid_input(test_name, size, interpolation, error, error_msg): 121 logger.info("Test Resize with bad input: {0}".format(test_name)) 122 with pytest.raises(error) as error_info: 123 vision.Resize(size, interpolation) 124 assert error_msg in str(error_info.value) 125 126 test_invalid_input("invalid size parameter type as a single number", 4.5, Inter.LINEAR, TypeError, 127 "Size should be a single integer or a list/tuple (h, w) of length 2.") 128 test_invalid_input("invalid size parameter shape", (2, 3, 4), Inter.LINEAR, TypeError, 129 "Size should be a single integer or a list/tuple (h, w) of length 2.") 130 test_invalid_input("invalid size parameter type in a tuple", (2.3, 3), Inter.LINEAR, TypeError, 131 "Argument size at dim 0 with value 2.3 is not of type [<class 'int'>]") 132 test_invalid_input("invalid Interpolation value", (2.3, 3), None, KeyError, "None") 133 134 135if __name__ == "__main__": 136 test_resize_op(plot=True) 137 test_resize_op_ANTIALIAS() 138 test_resize_md5(plot=True) 139 test_resize_op_invalid_input() 140