forked from mindspore-Ecosystem/mindspore
70 lines
2.6 KiB
C++
70 lines
2.6 KiB
C++
/**
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* 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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#include "common/common.h"
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#include "common/cvop_common.h"
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#include "minddata/dataset/kernels/image/random_crop_op.h"
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#include "utils/log_adapter.h"
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using namespace mindspore::dataset;
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class MindDataTestRandomCropOp : public UT::CVOP::CVOpCommon {
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protected:
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MindDataTestRandomCropOp() : CVOpCommon() {}
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TensorRow output_tensor_row;
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};
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/// Feature: RandomCrop op
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/// Description: Test RandomCropOp with crop size (128, 128) and padding = (0, 0, 0, 0)
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/// Expectation: Output is equal to the expected output
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TEST_F(MindDataTestRandomCropOp, TestOp1) {
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MS_LOG(INFO) << "Doing testRandomCrop.";
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// Crop params
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unsigned int crop_height = 128;
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unsigned int crop_width = 128;
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auto op = std::make_unique<RandomCropOp>(crop_height, crop_width, 0, 0, 0, 0, false, BorderType::kConstant);
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TensorRow input_tensor_row;
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input_tensor_row.push_back(input_tensor_);
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input_tensor_row.push_back(input_tensor_);
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Status s = op->Compute(input_tensor_row, &output_tensor_row);
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for (size_t i = 0; i < input_tensor_row.size(); i++) {
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size_t actual = 0;
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if (s == Status::OK()) {
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actual = output_tensor_row[i]->shape()[0] * output_tensor_row[i]->shape()[1] * output_tensor_row[i]->shape()[2];
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}
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EXPECT_EQ(actual, crop_height * crop_width * 3);
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EXPECT_EQ(s, Status::OK());
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}
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}
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/// Feature: RandomCrop op
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/// Description: Test RandomCropOp with crop size (1280, 1280) and padding = (513, 513, 513, 513)
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/// Expectation: Output is equal to the expected output
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TEST_F(MindDataTestRandomCropOp, TestOp2) {
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MS_LOG(INFO) << "Doing testRandomCrop.";
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// Crop params
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unsigned int crop_height = 1280;
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unsigned int crop_width = 1280;
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TensorRow input_tensor_row;
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input_tensor_row.push_back(input_tensor_);
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input_tensor_row.push_back(input_tensor_);
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auto op = std::make_unique<RandomCropOp>(
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crop_height, crop_width, 513, 513, 513, 513, false, BorderType::kConstant);
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Status s = op->Compute(input_tensor_row, &output_tensor_row);
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EXPECT_EQ(true, s.IsOk());
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MS_LOG(INFO) << "testRandomCrop end.";
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}
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