* -------------------------------------------------------------------------
* This file is part of the Vision SDK project.
* Copyright (c) 2025 Huawei Technologies Co.,Ltd.
*
* Vision SDK is licensed under Mulan PSL v2.
* You can use this software according to the terms and conditions of the Mulan PSL v2.
* You may obtain a copy of Mulan PSL v2 at:
*
* http://license.coscl.org.cn/MulanPSL2
*
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND,
* EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT,
* MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE.
* See the Mulan PSL v2 for more details.
* -------------------------------------------------------------------------
* Description: Gtest unit cases.
* Author: MindX SDK
* Create: 2020
* History: NA
*/
#include <random>
#include <glog/logging.h>
#include <gtest/gtest.h>
#include "MxBase/Log/Log.h"
#include "PostProcessUtils.h"
#include "ObjectPostProcessors/SsdMobilenetFpnMindsporePost.h"
namespace {
using namespace MxBase;
const float MIN_VALUE = 0.;
const float MAX_VALUE = 10.;
class SsdMobilenetFpnMindsporePostTest : public testing::Test {
public:
std::map<std::string, std::string> postConfig_ = {{"postProcessConfigContent",
"{\"CLASS_NUM\": \"80\","
"\"SCORE_THRESH\": \"0.7\","
"\"IOU_THRESH\": \"0.5\","
"\"RPN_MAX_NUM\": \"1000\","
"\"MAX_PER_IMG\": \"128\","
"\"MASK_THREAD_BINARY\": \"0.5\","
"\"MASK_SHAPE_SIZE\": \"28\"}"}};
};
TEST_F(SsdMobilenetFpnMindsporePostTest, SsdMobilenetFpnMindsporeTest)
{
SsdMobilenetFpnMindsporePost instanceSrc;
SsdMobilenetFpnMindsporePost instanceDst(instanceSrc);
instanceSrc = instanceDst;
EXPECT_TRUE(1);
}
TEST_F(SsdMobilenetFpnMindsporePostTest, Test_SsdMobilenetFpnMindsporeTest_Init_Should_Success)
{
SsdMobilenetFpnMindsporePost instanceSrc;
APP_ERROR ret = instanceSrc.Init(postConfig_);
EXPECT_EQ(ret, 0);
}
TEST_F(SsdMobilenetFpnMindsporePostTest, Test_SsdMobilenetFpnMindsporeTest_Should_Fail_When_Wrong_Json_Format)
{
SsdMobilenetFpnMindsporePost instanceSrc;
std::map<std::string, std::string> postConfig = {{"postProcessConfigContent",
"\"KEYPOINT_NUM\": \"17\","
"\"SCORE_THRESH\": \"0.1\"}"}};
APP_ERROR ret = instanceSrc.Init(postConfig);
EXPECT_NE(ret, 0);
}
TEST_F(SsdMobilenetFpnMindsporePostTest, Test_SsdMobilenetFpnMindsporeTest_Should_Fail_When_Wrong_Tensor_Shape)
{
LogInfo << "****************case SsdMobilenetFpnMindsporeTest***************";
SsdMobilenetFpnMindsporePost instanceSrc;
std::vector<uint32_t> shape = {1, 255, 255};
auto type = TensorDataType::TENSOR_DTYPE_FLOAT32;
TensorBase tensor(shape, type);
TensorBase::TensorBaseMalloc(tensor);
std::vector<TensorBase> vec = {tensor, tensor};
std::vector<std::vector<ObjectInfo>> objectInfos;
ResizedImageInfo resizedImageInfo = {16, 16, 32, 32, ResizeType::RESIZER_STRETCHING, 1.0};
std::vector<ResizedImageInfo> resizedImageInfos = {resizedImageInfo, resizedImageInfo};
std::map<std::string, std::shared_ptr<void>> configParamMap;
APP_ERROR ret = instanceSrc.Process(vec, objectInfos, resizedImageInfos, configParamMap);
EXPECT_NE(ret, 0);
}
TEST_F(SsdMobilenetFpnMindsporePostTest, Test_SsdMobilenetFpnMindsporeTest_Should_Fail_When_Wrong_Tensor_Num)
{
LogInfo << "****************case SsdMobilenetFpnMindsporeTest***************";
SsdMobilenetFpnMindsporePost instanceSrc;
std::vector<uint32_t> shape = {1, 255, 4};
auto type = TensorDataType::TENSOR_DTYPE_FLOAT32;
TensorBase tensor(shape, type);
TensorBase::TensorBaseMalloc(tensor);
std::vector<TensorBase> vec = {tensor};
std::vector<std::vector<ObjectInfo>> objectInfos;
ResizedImageInfo resizedImageInfo = {16, 16, 32, 32, ResizeType::RESIZER_STRETCHING, 1.0};
std::vector<ResizedImageInfo> resizedImageInfos = {resizedImageInfo, resizedImageInfo};
std::map<std::string, std::shared_ptr<void>> configParamMap;
APP_ERROR ret = instanceSrc.Process(vec, objectInfos, resizedImageInfos, configParamMap);
EXPECT_NE(ret, 0);
}
TEST_F(SsdMobilenetFpnMindsporePostTest, Test_SsdMobilenetFpnMindsporeTest_Should_Fail_When_Wrong_Tensor_DataType)
{
LogInfo << "****************case SsdMobilenetFpnMindsporeTest***************";
SsdMobilenetFpnMindsporePost instanceSrc;
std::vector<uint32_t> shape = {1, 255, 4};
auto type = TensorDataType::TENSOR_DTYPE_UINT8;
TensorBase tensor(shape, type);
TensorBase::TensorBaseMalloc(tensor);
std::vector<TensorBase> vec = {tensor};
std::vector<std::vector<ObjectInfo>> objectInfos;
ResizedImageInfo resizedImageInfo = {16, 16, 32, 32, ResizeType::RESIZER_STRETCHING, 1.0};
std::vector<ResizedImageInfo> resizedImageInfos = {resizedImageInfo, resizedImageInfo};
std::map<std::string, std::shared_ptr<void>> configParamMap;
auto ret = instanceSrc.Process(vec, objectInfos, resizedImageInfos, configParamMap);
EXPECT_NE(ret, 0);
}
TEST_F(SsdMobilenetFpnMindsporePostTest, Test_SsdMobilenetFpnMindsporeTest_Should_Fail_When_Wrong_Tensor_Shape1)
{
LogInfo << "****************case SsdMobilenetFpnMindsporeTest***************";
SsdMobilenetFpnMindsporePost instanceSrc;
std::vector<uint32_t> shape = {1, 255, 4};
auto type = TensorDataType::TENSOR_DTYPE_FLOAT32;
TensorBase tensor(shape, type);
TensorBase::TensorBaseMalloc(tensor);
std::vector<TensorBase> vec = {tensor, tensor};
std::vector<std::vector<ObjectInfo>> objectInfos;
ResizedImageInfo resizedImageInfo = {16, 16, 32, 32, ResizeType::RESIZER_STRETCHING, 1.0};
std::vector<ResizedImageInfo> resizedImageInfos = {resizedImageInfo, resizedImageInfo};
std::map<std::string, std::shared_ptr<void>> configParamMap;
APP_ERROR ret = instanceSrc.Process(vec, objectInfos, resizedImageInfos, configParamMap);
EXPECT_NE(ret, 0);
}
TEST_F(SsdMobilenetFpnMindsporePostTest, Test_SsdMobilenetFpnMindsporeTest_Should_Fail_When_Wrong_Tensor_BatchSize)
{
LogInfo << "****************case SsdMobilenetFpnMindsporeTest***************";
SsdMobilenetFpnMindsporePost instanceSrc;
APP_ERROR ret = instanceSrc.Init(postConfig_);
EXPECT_EQ(ret, 0);
std::vector<uint32_t> shape = {1, 255, 4};
std::vector<uint32_t> shape2 = {1, 255, 80};
auto type = TensorDataType::TENSOR_DTYPE_FLOAT32;
TensorBase tensor(shape, type);
TensorBase::TensorBaseMalloc(tensor);
TensorBase tensor2(shape2, type);
TensorBase::TensorBaseMalloc(tensor2);
std::vector<TensorBase> vec = {tensor, tensor2};
std::vector<std::vector<ObjectInfo>> objectInfos;
ResizedImageInfo resizedImageInfo = {16, 16, 32, 32, ResizeType::RESIZER_STRETCHING, 1.0};
std::vector<ResizedImageInfo> resizedImageInfos = {resizedImageInfo, resizedImageInfo};
std::map<std::string, std::shared_ptr<void>> configParamMap;
ret = instanceSrc.Process(vec, objectInfos, resizedImageInfos, configParamMap);
EXPECT_NE(ret, 0);
}
TEST_F(SsdMobilenetFpnMindsporePostTest, Test_SsdMobilenetFpnMindsporeTest_Should_Success)
{
LogInfo << "****************case SsdMobilenetFpnMindsporeTest***************";
SsdMobilenetFpnMindsporePost instanceSrc;
APP_ERROR ret = instanceSrc.Init(postConfig_);
EXPECT_EQ(ret, 0);
std::vector<uint32_t> shape = {2, 255, 4};
std::vector<uint32_t> shape2 = {2, 255, 80};
auto type = TensorDataType::TENSOR_DTYPE_FLOAT32;
TensorBase tensor1(shape, type);
TensorBase::TensorBaseMalloc(tensor1);
TensorBase tensor2(shape2, type);
TensorBase::TensorBaseMalloc(tensor2);
std::vector<TensorBase> vec = {tensor1, tensor2};
PostProcessUtils::SetRandomTensorValue<float>(vec, MIN_VALUE, MAX_VALUE);
std::vector<std::vector<ObjectInfo>> objectInfos;
ResizedImageInfo resizedImageInfo = {16, 16, 32, 32, ResizeType::RESIZER_STRETCHING, 1.0};
std::vector<ResizedImageInfo> resizedImageInfos = {resizedImageInfo, resizedImageInfo};
std::map<std::string, std::shared_ptr<void>> configParamMap;
ret = instanceSrc.Process(vec, objectInfos, resizedImageInfos, configParamMap);
EXPECT_EQ(ret, 0);
}
TEST_F(SsdMobilenetFpnMindsporePostTest, Test_SsdMobilenetFpnMindsporeTest_DeInit_Should_Success)
{
std::shared_ptr<SsdMobilenetFpnMindsporePost> instanceSrc = GetObjectInstance();
EXPECT_NE(instanceSrc, nullptr);
APP_ERROR ret = instanceSrc->DeInit();
EXPECT_EQ(ret, 0);
}
}
int main(int argc, char *argv[])
{
testing::InitGoogleTest(&argc, argv);
int ret = RUN_ALL_TESTS();
return ret;
}
