/** * Copyright 2019-2021 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #include #include #include #include "common/common.h" #include "utils/ms_utils.h" #include "minddata/dataset/core/client.h" #include "minddata/dataset/engine/datasetops/source/voc_op.h" #include "minddata/dataset/engine/datasetops/source/sampler/sampler.h" #include "minddata/dataset/include/dataset/datasets.h" #include "minddata/dataset/util/status.h" #include "gtest/gtest.h" #include "utils/log_adapter.h" #include "securec.h" namespace common = mindspore::common; using namespace mindspore::dataset; using mindspore::LogStream; using mindspore::ExceptionType::NoExceptionType; using mindspore::MsLogLevel::ERROR; std::shared_ptr Build(std::vector> ops); class MindDataTestVOCOp : public UT::DatasetOpTesting { protected: }; TEST_F(MindDataTestVOCOp, TestVOCDetection) { std::string dataset_path; dataset_path = datasets_root_path_ + "/testVOC2012"; std::shared_ptr ds = VOC(dataset_path, "Detection", "train", {}, false, std::make_shared(0, 0)); EXPECT_NE(ds, nullptr); std::shared_ptr iter = ds->CreateIterator(); EXPECT_NE(iter, nullptr); std::unordered_map row; ASSERT_OK(iter->GetNextRow(&row)); int row_count = 0; while (row.size() != 0) { auto image = row["image"]; auto label = row["label"]; MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); MS_LOG(INFO) << "Tensor label shape: " << label.Shape(); ASSERT_OK(iter->GetNextRow(&row)); row_count++; } ASSERT_EQ(row_count, 9); iter->Stop(); } TEST_F(MindDataTestVOCOp, TestVOCSegmentation) { std::string dataset_path; dataset_path = datasets_root_path_ + "/testVOC2012"; std::shared_ptr ds = VOC(dataset_path, "Segmentation", "train", {}, false, std::make_shared(0, 0)); EXPECT_NE(ds, nullptr); std::shared_ptr iter = ds->CreateIterator(); EXPECT_NE(iter, nullptr); std::unordered_map row; ASSERT_OK(iter->GetNextRow(&row)); int row_count = 0; while (!row.empty()) { auto image = row["image"]; auto target = row["target"]; MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); MS_LOG(INFO) << "Tensor target shape: " << target.Shape(); ASSERT_OK(iter->GetNextRow(&row)); row_count++; } ASSERT_EQ(row_count, 10); iter->Stop(); } TEST_F(MindDataTestVOCOp, TestVOCClassIndex) { std::string dataset_path; dataset_path = datasets_root_path_ + "/testVOC2012"; std::map class_index; class_index["car"] = 0; class_index["cat"] = 1; class_index["train"] = 5; std::shared_ptr ds = VOC(dataset_path, "Detection", "train", class_index, false, std::make_shared(0, 0)); EXPECT_NE(ds, nullptr); std::shared_ptr iter = ds->CreateIterator(); EXPECT_NE(iter, nullptr); std::unordered_map row; ASSERT_OK(iter->GetNextRow(&row)); int row_count = 0; while (!row.empty()) { auto image = row["image"]; auto label = row["label"]; MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); MS_LOG(INFO) << "Tensor label shape: " << label.Shape(); ASSERT_OK(iter->GetNextRow(&row)); row_count++; } ASSERT_EQ(row_count, 6); iter->Stop(); }