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212 lines
6.6 KiB
212 lines
6.6 KiB
/**
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* Copyright 2019-2021 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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#include <fstream>
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#include <iostream>
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#include <memory>
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#include <string>
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#include "common/common.h"
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#include "utils/ms_utils.h"
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#include "minddata/dataset/core/client.h"
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#include "minddata/dataset/core/global_context.h"
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#include "minddata/dataset/engine/datasetops/source/voc_op.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/distributed_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/pk_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/random_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/sequential_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/subset_random_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/weighted_random_sampler.h"
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#include "minddata/dataset/util/path.h"
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#include "minddata/dataset/util/status.h"
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#include "gtest/gtest.h"
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#include "utils/log_adapter.h"
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#include "securec.h"
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namespace common = mindspore::common;
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using namespace mindspore::dataset;
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using mindspore::MsLogLevel::ERROR;
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using mindspore::ExceptionType::NoExceptionType;
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using mindspore::LogStream;
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std::shared_ptr<BatchOp> Batch(int batch_size = 1, bool drop = false, int rows_per_buf = 2);
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std::shared_ptr<ExecutionTree> Build(std::vector<std::shared_ptr<DatasetOp>> ops);
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class MindDataTestVOCOp : public UT::DatasetOpTesting {
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protected:
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};
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TEST_F(MindDataTestVOCOp, TestVOCDetection) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testVOC2012";
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std::string task_type("Detection");
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std::string task_mode("train");
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std::shared_ptr<VOCOp> my_voc_op;
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VOCOp::Builder builder;
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Status rc = builder.SetDir(dataset_path).SetTask(task_type).SetUsage(task_mode)
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.Build(&my_voc_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_voc_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_voc_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(DEBUG) << "Launch tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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MS_LOG(DEBUG) << "Row display for row #: " << row_count << ".";
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//Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(DEBUG) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 9);
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}
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TEST_F(MindDataTestVOCOp, TestVOCSegmentation) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testVOC2012";
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std::string task_type("Segmentation");
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std::string task_mode("train");
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std::shared_ptr<VOCOp> my_voc_op;
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VOCOp::Builder builder;
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Status rc = builder.SetDir(dataset_path).SetTask(task_type).SetUsage(task_mode)
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.Build(&my_voc_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_voc_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_voc_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(DEBUG) << "Launch tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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MS_LOG(DEBUG) << "Row display for row #: " << row_count << ".";
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//Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(DEBUG) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 10);
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}
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TEST_F(MindDataTestVOCOp, TestVOCClassIndex) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testVOC2012";
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std::string task_type("Detection");
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std::string task_mode("train");
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std::map<std::string, int32_t> class_index;
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class_index["car"] = 0;
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class_index["cat"] = 1;
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class_index["train"] = 5;
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std::shared_ptr<VOCOp> my_voc_op;
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VOCOp::Builder builder;
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Status rc =
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builder.SetDir(dataset_path).SetTask(task_type).SetUsage(task_mode)
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.SetClassIndex(class_index)
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.Build(&my_voc_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_voc_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_voc_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(DEBUG) << "Launch tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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MS_LOG(DEBUG) << "Row display for row #: " << row_count << ".";
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//Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(DEBUG) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 6);
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}
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