Files
FastDeploy/benchmark/cpp/benchmark_ppocr_det.cc
WJJ1995 fe9aff15f2 [Benchmark] Add SaveBenchmarkResult func for benchmark (#1442)
* add GPL lisence

* add GPL-3.0 lisence

* add GPL-3.0 lisence

* add GPL-3.0 lisence

* support yolov8

* add pybind for yolov8

* add yolov8 readme

* add cpp benchmark

* add cpu and gpu mem

* public part split

* add runtime mode

* fixed bugs

* add cpu_thread_nums

* deal with comments

* deal with comments

* deal with comments

* rm useless code

* add FASTDEPLOY_DECL

* add FASTDEPLOY_DECL

* fixed for windows

* mv rss to pss

* mv rss to pss

* Update utils.cc

* use thread to collect mem

* Add ResourceUsageMonitor

* rm useless code

* fixed bug

* fixed typo

* update ResourceUsageMonitor

* fixed bug

* fixed bug

* add note for ResourceUsageMonitor

* deal with comments

* add macros

* deal with comments

* deal with comments

* deal with comments

* re-lint

* rm pmap and use mem api

* rm pmap and use mem api

* add mem api

* Add PrintBenchmarkInfo func

* Add PrintBenchmarkInfo func

* Add PrintBenchmarkInfo func

* deal with comments

* fixed enable_paddle_to_trt

* add log for paddle_trt

* support ppcls benchmark

* use new trt option api

* update benchmark info

* simplify benchmark.cc

* simplify benchmark.cc

* deal with comments

* Add ppseg && ppocr benchmark

* add OCR rec img

* add ocr benchmark

* fixed trt shape

* add trt shape

* resolve conflict

* add ENABLE_BENCHMARK define

* Add ClassifyDiff

* Add Resize for ClassifyResult

* deal with comments

* add convert info script

* resolve conflict

* Add SaveBenchmarkResult func

* fixed bug

* fixed bug

* fixed bug

---------

Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
2023-02-28 11:55:22 +08:00

63 lines
2.5 KiB
C++
Executable File

// 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);
// Detection Model
auto det_model_file = FLAGS_model + sep + "inference.pdmodel";
auto det_params_file = FLAGS_model + sep + "inference.pdiparams";
if (FLAGS_backend == "paddle_trt") {
option.paddle_infer_option.collect_trt_shape = true;
}
if (FLAGS_backend == "paddle_trt" || FLAGS_backend == "trt") {
option.trt_option.SetShape("x", {1, 3, 64, 64}, {1, 3, 640, 640},
{1, 3, 960, 960});
}
auto model_ppocr_det =
vision::ocr::DBDetector(det_model_file, det_params_file, option);
std::vector<std::array<int, 8>> res;
// Run once at least
model_ppocr_det.Predict(im, &res);
// 1. Test result diff
std::cout << "=============== Test result diff =================\n";
// Save result to -> disk.
std::string ppocr_det_result_path = "ppocr_det_result.txt";
benchmark::ResultManager::SaveOCRDetResult(res, ppocr_det_result_path);
// Load result from <- disk.
std::vector<std::array<int, 8>> res_loaded;
benchmark::ResultManager::LoadOCRDetResult(&res_loaded,
ppocr_det_result_path);
// Calculate diff between two results.
auto ppocr_det_diff =
benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
std::cout << "PPOCR Boxes diff: mean=" << ppocr_det_diff.boxes.mean
<< ", max=" << ppocr_det_diff.boxes.max
<< ", min=" << ppocr_det_diff.boxes.min << std::endl;
BENCHMARK_MODEL(model_ppocr_det, model_ppocr_det.Predict(im, &res));
#endif
return 0;
}