mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 03:46:40 +08:00
ee85a3cade
* [Benchmark] Init benchmark precision api * [Benchmark] Init benchmark precision api * [Benchmark] Add benchmark precision api * [Benchmark] Calculate the statis of diff * [Benchmark] Calculate the statis of diff * [Benchmark] Calculate the statis of diff * [Benchmark] Calculate the statis of diff * [Benchmark] Calculate the statis of diff * [Benchmark] Add SplitDataLine utils * [Benchmark] Add LexSortByXY func * [Benchmark] Add LexSortByXY func * [Benchmark] Add LexSortDetectionResultByXY func * [Benchmark] Add LexSortDetectionResultByXY func * [Benchmark] Add tensor diff presicion test * [Benchmark] fixed conflicts * [Benchmark] fixed calc tensor diff * fixed build bugs * fixed ci bugs when WITH_TESTING=ON
87 lines
3.6 KiB
C++
87 lines
3.6 KiB
C++
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
|
|
//
|
|
// 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 "flags.h"
|
|
#include "macros.h"
|
|
#include "option.h"
|
|
|
|
namespace vision = fastdeploy::vision;
|
|
namespace benchmark = fastdeploy::benchmark;
|
|
|
|
int main(int argc, char* argv[]) {
|
|
#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
|
|
// Initialization
|
|
auto option = fastdeploy::RuntimeOption();
|
|
if (!CreateRuntimeOption(&option, argc, argv, true)) {
|
|
return -1;
|
|
}
|
|
auto im = cv::imread(FLAGS_image);
|
|
auto model_file = FLAGS_model + sep + "model.pdmodel";
|
|
auto params_file = FLAGS_model + sep + "model.pdiparams";
|
|
auto config_file = FLAGS_model + sep + "infer_cfg.yml";
|
|
auto model_ppyolov8 = vision::detection::PaddleYOLOv8(model_file, params_file,
|
|
config_file, option);
|
|
vision::DetectionResult res;
|
|
// Run once at least
|
|
model_ppyolov8.Predict(im, &res);
|
|
// 1. Test result diff
|
|
std::cout << "=============== Test result diff =================\n";
|
|
// Save result to -> disk.
|
|
std::string det_result_path = "ppyolov8_result.txt";
|
|
benchmark::ResultManager::SaveDetectionResult(res, det_result_path);
|
|
// Load result from <- disk.
|
|
vision::DetectionResult res_loaded;
|
|
benchmark::ResultManager::LoadDetectionResult(&res_loaded, det_result_path);
|
|
// Calculate diff between two results.
|
|
auto det_diff =
|
|
benchmark::ResultManager::CalculateDiffStatis(&res, &res_loaded);
|
|
std::cout << "diff: mean=" << det_diff.mean << ",max=" << det_diff.max
|
|
<< ",min=" << det_diff.min << std::endl;
|
|
// 2. Test tensor diff
|
|
std::cout << "=============== Test tensor diff =================\n";
|
|
std::vector<vision::DetectionResult> bacth_res;
|
|
std::vector<fastdeploy::FDTensor> input_tensors, output_tensors;
|
|
std::vector<cv::Mat> imgs;
|
|
imgs.push_back(im);
|
|
std::vector<vision::FDMat> fd_images = vision::WrapMat(imgs);
|
|
|
|
model_ppyolov8.GetPreprocessor().Run(&fd_images, &input_tensors);
|
|
input_tensors[0].name = "image";
|
|
input_tensors[1].name = "scale_factor";
|
|
input_tensors[2].name = "im_shape";
|
|
input_tensors.pop_back();
|
|
model_ppyolov8.Infer(input_tensors, &output_tensors);
|
|
model_ppyolov8.GetPostprocessor().Run(output_tensors, &bacth_res);
|
|
// Save tensor to -> disk.
|
|
auto& tensor_dump = output_tensors[0];
|
|
std::string det_tensor_path = "ppyolov8_tensor.txt";
|
|
benchmark::ResultManager::SaveFDTensor(tensor_dump, det_tensor_path);
|
|
// Load tensor from <- disk.
|
|
fastdeploy::FDTensor tensor_loaded;
|
|
benchmark::ResultManager::LoadFDTensor(&tensor_loaded, det_tensor_path);
|
|
// Calculate diff between two tensors.
|
|
auto det_tensor_diff = benchmark::ResultManager::CalculateDiffStatis(
|
|
&tensor_dump, &tensor_loaded);
|
|
std::cout << "diff: mean=" << det_tensor_diff.mean
|
|
<< ",max=" << det_tensor_diff.max << ",min=" << det_tensor_diff.min
|
|
<< std::endl;
|
|
// 3. Run profiling
|
|
BENCHMARK_MODEL(model_ppyolov8, model_ppyolov8.Predict(im, &res))
|
|
auto vis_im = vision::VisDetection(im, res);
|
|
cv::imwrite("vis_result.jpg", vis_im);
|
|
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
|
|
#endif
|
|
|
|
return 0;
|
|
} |