1 /**
2 * Copyright 2019 Huawei Technologies Co., Ltd
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16 #include "common/common.h"
17 #include "common/cvop_common.h"
18 #include "minddata/dataset/kernels/image/center_crop_op.h"
19 #include "minddata/dataset/core/cv_tensor.h"
20 #include "utils/log_adapter.h"
21
22 using namespace mindspore::dataset;
23 using mindspore::LogStream;
24 using mindspore::ExceptionType::NoExceptionType;
25 using mindspore::MsLogLevel::INFO;
26
27 class MindDataTestCenterCropOp : public UT::CVOP::CVOpCommon {
28 public:
MindDataTestCenterCropOp()29 MindDataTestCenterCropOp() : CVOpCommon() {}
30 };
31
TEST_F(MindDataTestCenterCropOp,TestOp1)32 TEST_F(MindDataTestCenterCropOp, TestOp1) {
33 MS_LOG(INFO) << "Doing MindDataTestCenterCropOp::TestOp1.";
34 std::shared_ptr<Tensor> output_tensor;
35 int het = 256;
36 int wid = 128;
37 std::unique_ptr<CenterCropOp> op(new CenterCropOp(het, wid));
38 EXPECT_TRUE(op->OneToOne());
39 Status s = op->Compute(input_tensor_, &output_tensor);
40 EXPECT_TRUE(s.IsOk());
41 EXPECT_EQ(het, output_tensor->shape()[0]);
42 EXPECT_EQ(wid, output_tensor->shape()[1]);
43 std::shared_ptr<CVTensor> p = CVTensor::AsCVTensor(output_tensor);
44 }
45
TEST_F(MindDataTestCenterCropOp,TestOp2)46 TEST_F(MindDataTestCenterCropOp, TestOp2) {
47 MS_LOG(INFO) << "MindDataTestCenterCropOp::TestOp2. Cap valid crop size at 10 times the input size";
48 std::shared_ptr<Tensor> output_tensor;
49
50 int64_t wid = input_tensor_->shape()[0] * 10 + 1;
51 int64_t het = input_tensor_->shape()[1] * 10 + 1;
52
53 std::unique_ptr<CenterCropOp> op(new CenterCropOp(het, wid));
54 Status s = op->Compute(input_tensor_, &output_tensor);
55 EXPECT_TRUE(s.IsError());
56 ASSERT_TRUE(s.StatusCode() == StatusCode::kMDUnexpectedError);
57 }
58
TEST_F(MindDataTestCenterCropOp,TestOp3)59 TEST_F(MindDataTestCenterCropOp, TestOp3) {
60 MS_LOG(INFO) << "Doing MindDataTestCenterCropOp::TestOp3. Test single integer input for square crop.";
61 std::shared_ptr<Tensor> output_tensor;
62 int side = 128;
63 std::unique_ptr<CenterCropOp> op(new CenterCropOp(side));
64 EXPECT_TRUE(op->OneToOne());
65 Status s = op->Compute(input_tensor_, &output_tensor);
66 EXPECT_TRUE(s.IsOk());
67 // Confirm both height and width are of size <side>.
68 EXPECT_EQ(side, output_tensor->shape()[0]);
69 EXPECT_EQ(side, output_tensor->shape()[1]);
70 std::shared_ptr<CVTensor> p = CVTensor::AsCVTensor(output_tensor);
71 }
72