127 lines
4.3 KiB
Python
127 lines
4.3 KiB
Python
# Copyright 2021-2022 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 Crop op in DE
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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 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_crop_pipeline(plot=False):
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"""
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Feature: Crop op
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Description: Test Crop op in pipeline mode
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Expectation: Passes the equality test
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"""
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logger.info("test_crop_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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crop_op = c_vision.Crop((0, 0), (20, 25))
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dataset1 = dataset1.map(operations=decode_op, input_columns=["image"])
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dataset1 = dataset1.map(operations=crop_op, input_columns=["image"])
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# Second dataset
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dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=[
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"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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crop_ms = data1["image"]
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original = data2["image"]
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crop_expect = original[0:20, 0:25]
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mse = diff_mse(crop_ms, crop_expect)
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logger.info("crop_{}, 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, crop_ms, mse, crop_expect)
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def test_crop_eager():
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"""
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Feature: Crop op
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Description: Test Crop op in eager mode
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Expectation: Passes the equality test
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"""
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logger.info("test_crop_eager")
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img = cv2.imread(IMAGE_FILE)
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img_ms = c_vision.Crop((20, 50), (30, 50))(img)
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img_expect = img[20:50, 50:100]
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mse = diff_mse(img_ms, img_expect)
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assert mse == 0
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def test_crop_exception():
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"""
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Feature: Crop op
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Description: Test Crop op with invalid parameters
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Expectation: Correct error and message are thrown as expected
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"""
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logger.info("test_crop_exception")
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try:
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_ = c_vision.Crop([-10, 0], [20])
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except ValueError as e:
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logger.info("Got an exception in Crop: {}".format(str(e)))
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assert "not within the required interval of [0, 2147483647]" in str(e)
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try:
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_ = c_vision.Crop([0, 5.2], [10, 10])
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except TypeError as e:
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logger.info("Got an exception in Crop: {}".format(str(e)))
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assert "not of type [<class 'int'>]" in str(e)
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try:
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_ = c_vision.Crop([0], [28])
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except TypeError as e:
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logger.info("Got an exception in Crop: {}".format(str(e)))
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assert "Coordinates should be a list/tuple (y, x) of length 2." in str(
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e)
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try:
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_ = c_vision.Crop((0, 0), -1)
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except ValueError as e:
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logger.info("Got an exception in Crop: {}".format(str(e)))
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assert "not within the required interval of [1, 16777216]" in str(e)
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try:
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_ = c_vision.Crop((0, 0), (10.5, 15))
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except TypeError as e:
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logger.info("Got an exception in Crop: {}".format(str(e)))
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assert "not of type [<class 'int'>]" in str(e)
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try:
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_ = c_vision.Crop((0, 0), (0, 10, 20))
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except TypeError as e:
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logger.info("Got an exception in Crop: {}".format(str(e)))
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assert "Size should be a single integer or a list/tuple (h, w) of length 2." in str(
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e)
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if __name__ == "__main__":
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test_crop_pipeline(plot=False)
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test_crop_eager()
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test_crop_exception()
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