mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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e3b285c762
* Support PETR v2 * make petrv2 precision equal with the origin repo * delete extra func * modify review problem * delete visualize * Update README_CN.md * Update README.md * Update README_CN.md * fix build problem * delete external variable and function --------- Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
85 lines
2.9 KiB
C++
85 lines
2.9 KiB
C++
// Copyright (c) 2022 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 "fastdeploy/vision.h"
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#ifdef WIN32
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const char sep = '\\';
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#else
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const char sep = '/';
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#endif
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void InitAndInfer(const std::string& model_dir, const std::string& images_dir,
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const fastdeploy::RuntimeOption& option) {
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auto model_file = model_dir + sep + "petrv2_inference.pdmodel";
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auto params_file = model_dir + sep + "petrv2_inference.pdiparams";
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auto config_file = model_dir + sep + "infer_cfg.yml";
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fastdeploy::vision::EnableFlyCV();
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auto model = fastdeploy::vision::perception::Petr(
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model_file, params_file, config_file, option,
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fastdeploy::ModelFormat::PADDLE);
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assert(model.Initialized());
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std::vector<cv::Mat> im_batch;
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for (int i = 0; i < 12; i++) {
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auto image_file = images_dir + sep + "image" + std::to_string(i) + ".png";
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auto im = cv::imread(image_file);
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im_batch.emplace_back(im);
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}
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std::vector<fastdeploy::vision::PerceptionResult> res;
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if (!model.BatchPredict(im_batch, &res)) {
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std::cerr << "Failed to predict." << std::endl;
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return;
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}
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std::cout << res[0].Str() << std::endl;
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}
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int main(int argc, char* argv[]) {
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if (argc < 4) {
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std::cout << "Usage: infer_demo path/to/paddle_model"
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"path/to/image "
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"run_option, "
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"e.g ./infer_demo ./petr ./00000.png 0"
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<< std::endl;
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std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
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"with gpu; 2: run with paddle-trt"
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<< std::endl;
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return -1;
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}
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fastdeploy::RuntimeOption option;
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if (std::atoi(argv[3]) == 0) {
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option.UseCpu();
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} else if (std::atoi(argv[3]) == 1) {
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option.UseGpu();
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} else if (std::atoi(argv[3]) == 2) {
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option.UseGpu();
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option.UseTrtBackend();
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option.EnablePaddleToTrt();
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option.SetTrtInputShape("images", {1, 3, 384, 1280});
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option.SetTrtInputShape("down_ratios", {1, 2});
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option.SetTrtInputShape("trans_cam_to_img", {1, 3, 3});
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option.SetTrtInputData("trans_cam_to_img",
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{721.53771973, 0., 609.55932617, 0., 721.53771973,
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172.85400391, 0, 0, 1});
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option.EnablePaddleTrtCollectShape();
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}
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option.UsePaddleBackend();
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std::string model_dir = argv[1];
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std::string test_image = argv[2];
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InitAndInfer(model_dir, test_image, option);
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return 0;
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}
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