mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 11:56:44 +08:00
d3845eb4e1
* avoid mem copy for cpp benchmark * set CMAKE_BUILD_TYPE to Release * Add SegmentationDiff * change pointer to reference * fixed bug * cast uint8 to int32 * Add diff compare for OCR * Add diff compare for OCR * rm ppocr pipeline * Add yolov5 diff compare * Add yolov5 diff compare * deal with comments * deal with comments * fixed bug * fixed bug
63 lines
2.5 KiB
C++
63 lines
2.5 KiB
C++
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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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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#include "flags.h"
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#include "macros.h"
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#include "option.h"
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namespace vision = fastdeploy::vision;
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namespace benchmark = fastdeploy::benchmark;
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int main(int argc, char* argv[]) {
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#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
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// Initialization
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auto option = fastdeploy::RuntimeOption();
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if (!CreateRuntimeOption(&option, argc, argv, true)) {
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return -1;
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}
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auto im = cv::imread(FLAGS_image);
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// Detection Model
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auto det_model_file = FLAGS_model + sep + "inference.pdmodel";
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auto det_params_file = FLAGS_model + sep + "inference.pdiparams";
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if (FLAGS_backend == "paddle_trt") {
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option.paddle_infer_option.collect_trt_shape = true;
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}
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if (FLAGS_backend == "paddle_trt" || FLAGS_backend == "trt") {
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option.trt_option.SetShape("x", {1, 3, 64, 64}, {1, 3, 640, 640},
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{1, 3, 960, 960});
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}
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auto model_ppocr_det =
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vision::ocr::DBDetector(det_model_file, det_params_file, option);
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std::vector<std::array<int, 8>> res;
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// Run once at least
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model_ppocr_det.Predict(im, &res);
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// 1. Test result diff
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std::cout << "=============== Test result diff =================\n";
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// Save result to -> disk.
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std::string ppocr_det_result_path = "ppocr_det_result.txt";
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benchmark::ResultManager::SaveOCRDetResult(res, ppocr_det_result_path);
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// Load result from <- disk.
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std::vector<std::array<int, 8>> res_loaded;
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benchmark::ResultManager::LoadOCRDetResult(&res_loaded,
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ppocr_det_result_path);
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// Calculate diff between two results.
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auto ppocr_det_diff =
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benchmark::ResultManager::CalculateDiffStatis(res, res_loaded);
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std::cout << "PPOCR Boxes diff: mean=" << ppocr_det_diff.boxes.mean
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<< ", max=" << ppocr_det_diff.boxes.max
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<< ", min=" << ppocr_det_diff.boxes.min << std::endl;
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BENCHMARK_MODEL(model_ppocr_det, model_ppocr_det.Predict(im, &res));
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#endif
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return 0;
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} |