forked from huawei/mindspore2022
80 lines
2.8 KiB
Python
80 lines
2.8 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""
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Testing HorizontalFlip Python API
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"""
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import cv2
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import mindspore.dataset as ds
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import mindspore.dataset.vision.c_transforms as c_vision
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from mindspore import log as logger
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from util import visualize_image, diff_mse
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DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
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SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
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IMAGE_FILE = "../data/dataset/apple.jpg"
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def test_horizontal_flip_pipeline(plot=False):
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"""
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Test HorizontalFlip of c_transforms
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"""
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logger.info("test_horizontal_flip_pipeline")
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# First dataset
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dataset1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
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decode_op = c_vision.Decode()
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horizontal_flip_op = c_vision.HorizontalFlip()
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dataset1 = dataset1.map(operations=decode_op, input_columns=["image"])
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dataset1 = dataset1.map(operations=horizontal_flip_op, input_columns=["image"])
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# Second dataset
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dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
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dataset2 = dataset2.map(operations=decode_op, input_columns=["image"])
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num_iter = 0
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for data1, data2 in zip(dataset1.create_dict_iterator(num_epochs=1, output_numpy=True),
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dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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if num_iter > 0:
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break
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horizontal_flip_ms = data1["image"]
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original = data2["image"]
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horizontal_flip_cv = cv2.flip(original, 1)
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mse = diff_mse(horizontal_flip_ms, horizontal_flip_cv)
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logger.info("horizontal_flip_{}, mse: {}".format(num_iter + 1, mse))
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assert mse == 0
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num_iter += 1
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if plot:
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visualize_image(original, horizontal_flip_ms, mse, horizontal_flip_cv)
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def test_horizontal_flip_eager():
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"""
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Test HorizontalFlip with eager mode
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"""
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logger.info("test_horizontal_flip_eager")
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img = cv2.imread(IMAGE_FILE)
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img_ms = c_vision.HorizontalFlip()(img)
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img_cv = cv2.flip(img, 1)
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mse = diff_mse(img_ms, img_cv)
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assert mse == 0
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if __name__ == "__main__":
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test_horizontal_flip_pipeline(plot=False)
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test_horizontal_flip_eager()
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