mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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7b15f72516
* [FlyCV] Bump up FlyCV -> official release 1.0.0 * add seg models for XPU * add ocr model for XPU * add matting * add matting python * fix infer.cc * add keypointdetection support for XPU * Add adaface support for XPU * add ernie-3.0 * fix doc Co-authored-by: DefTruth <qiustudent_r@163.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
192 lines
6.9 KiB
C++
Executable File
192 lines
6.9 KiB
C++
Executable File
/***************************************************************************
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*
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* Copyright (c) 2021 Baidu.com, Inc. All Rights Reserved
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*
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**************************************************************************/
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/**
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* @author Baidu
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* @brief demo_image_inference
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*
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**/
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#include "fastdeploy/vision.h"
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void CpuInfer(const std::string &model_file, const std::string ¶ms_file,
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const std::vector<std::string> &image_file) {
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auto option = fastdeploy::RuntimeOption();
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auto model = fastdeploy::vision::faceid::AdaFace(model_file, params_file);
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if (!model.Initialized()) {
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std::cerr << "Failed to initialize." << std::endl;
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return;
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}
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cv::Mat face0 = cv::imread(image_file[0]);
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cv::Mat face1 = cv::imread(image_file[1]);
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cv::Mat face2 = cv::imread(image_file[2]);
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fastdeploy::vision::FaceRecognitionResult res0;
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fastdeploy::vision::FaceRecognitionResult res1;
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fastdeploy::vision::FaceRecognitionResult res2;
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if ((!model.Predict(&face0, &res0)) || (!model.Predict(&face1, &res1)) ||
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(!model.Predict(&face2, &res2))) {
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std::cerr << "Prediction Failed." << std::endl;
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}
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std::cout << "Prediction Done!" << std::endl;
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std::cout << "--- [Face 0]:" << res0.Str();
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std::cout << "--- [Face 1]:" << res1.Str();
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std::cout << "--- [Face 2]:" << res2.Str();
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float cosine01 = fastdeploy::vision::utils::CosineSimilarity(
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res0.embedding, res1.embedding, model.l2_normalize);
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float cosine02 = fastdeploy::vision::utils::CosineSimilarity(
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res0.embedding, res2.embedding, model.l2_normalize);
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std::cout << "Detect Done! Cosine 01: " << cosine01
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<< ", Cosine 02:" << cosine02 << std::endl;
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}
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void XpuInfer(const std::string &model_file, const std::string ¶ms_file,
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const std::vector<std::string> &image_file) {
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auto option = fastdeploy::RuntimeOption();
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option.UseXpu();
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auto model = fastdeploy::vision::faceid::AdaFace(model_file, params_file);
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if (!model.Initialized()) {
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std::cerr << "Failed to initialize." << std::endl;
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return;
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}
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cv::Mat face0 = cv::imread(image_file[0]);
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cv::Mat face1 = cv::imread(image_file[1]);
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cv::Mat face2 = cv::imread(image_file[2]);
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fastdeploy::vision::FaceRecognitionResult res0;
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fastdeploy::vision::FaceRecognitionResult res1;
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fastdeploy::vision::FaceRecognitionResult res2;
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if ((!model.Predict(&face0, &res0)) || (!model.Predict(&face1, &res1)) ||
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(!model.Predict(&face2, &res2))) {
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std::cerr << "Prediction Failed." << std::endl;
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}
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std::cout << "Prediction Done!" << std::endl;
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std::cout << "--- [Face 0]:" << res0.Str();
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std::cout << "--- [Face 1]:" << res1.Str();
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std::cout << "--- [Face 2]:" << res2.Str();
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float cosine01 = fastdeploy::vision::utils::CosineSimilarity(
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res0.embedding, res1.embedding, model.l2_normalize);
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float cosine02 = fastdeploy::vision::utils::CosineSimilarity(
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res0.embedding, res2.embedding, model.l2_normalize);
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std::cout << "Detect Done! Cosine 01: " << cosine01
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<< ", Cosine 02:" << cosine02 << std::endl;
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}
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void GpuInfer(const std::string &model_file, const std::string ¶ms_file,
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const std::vector<std::string> &image_file) {
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auto option = fastdeploy::RuntimeOption();
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option.UseGpu();
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auto model =
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fastdeploy::vision::faceid::AdaFace(model_file, params_file, option);
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if (!model.Initialized()) {
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std::cerr << "Failed to initialize." << std::endl;
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return;
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}
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cv::Mat face0 = cv::imread(image_file[0]);
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cv::Mat face1 = cv::imread(image_file[1]);
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cv::Mat face2 = cv::imread(image_file[2]);
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fastdeploy::vision::FaceRecognitionResult res0;
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fastdeploy::vision::FaceRecognitionResult res1;
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fastdeploy::vision::FaceRecognitionResult res2;
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if ((!model.Predict(&face0, &res0)) || (!model.Predict(&face1, &res1)) ||
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(!model.Predict(&face2, &res2))) {
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std::cerr << "Prediction Failed." << std::endl;
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}
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std::cout << "Prediction Done!" << std::endl;
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std::cout << "--- [Face 0]:" << res0.Str();
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std::cout << "--- [Face 1]:" << res1.Str();
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std::cout << "--- [Face 2]:" << res2.Str();
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float cosine01 = fastdeploy::vision::utils::CosineSimilarity(
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res0.embedding, res1.embedding, model.l2_normalize);
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float cosine02 = fastdeploy::vision::utils::CosineSimilarity(
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res0.embedding, res2.embedding, model.l2_normalize);
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std::cout << "Detect Done! Cosine 01: " << cosine01
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<< ", Cosine 02:" << cosine02 << std::endl;
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}
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void TrtInfer(const std::string &model_file, const std::string ¶ms_file,
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const std::vector<std::string> &image_file) {
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auto option = fastdeploy::RuntimeOption();
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option.UseGpu();
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option.UseTrtBackend();
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option.SetTrtInputShape("data", {1, 3, 112, 112});
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auto model =
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fastdeploy::vision::faceid::AdaFace(model_file, params_file, option);
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if (!model.Initialized()) {
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std::cerr << "Failed to initialize." << std::endl;
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return;
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}
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cv::Mat face0 = cv::imread(image_file[0]);
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cv::Mat face1 = cv::imread(image_file[1]);
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cv::Mat face2 = cv::imread(image_file[2]);
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fastdeploy::vision::FaceRecognitionResult res0;
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fastdeploy::vision::FaceRecognitionResult res1;
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fastdeploy::vision::FaceRecognitionResult res2;
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if ((!model.Predict(&face0, &res0)) || (!model.Predict(&face1, &res1)) ||
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(!model.Predict(&face2, &res2))) {
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std::cerr << "Prediction Failed." << std::endl;
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}
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std::cout << "Prediction Done!" << std::endl;
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std::cout << "--- [Face 0]:" << res0.Str();
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std::cout << "--- [Face 1]:" << res1.Str();
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std::cout << "--- [Face 2]:" << res2.Str();
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float cosine01 = fastdeploy::vision::utils::CosineSimilarity(
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res0.embedding, res1.embedding, model.l2_normalize);
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float cosine02 = fastdeploy::vision::utils::CosineSimilarity(
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res0.embedding, res2.embedding, model.l2_normalize);
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std::cout << "Detect Done! Cosine 01: " << cosine01
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<< ", Cosine 02:" << cosine02 << std::endl;
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}
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int main(int argc, char *argv[]) {
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if (argc < 7) {
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std::cout << "Usage: infer_demo path/to/model path/to/image run_option, "
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"e.g ./infer_demo mobilefacenet_adaface.pdmodel "
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"mobilefacenet_adaface.pdiparams "
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"test_lite_focal_AdaFace_0.JPG test_lite_focal_AdaFace_1.JPG "
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"test_lite_focal_AdaFace_2.JPG 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 gpu and use tensorrt backend; 3: run with xpu."
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<< std::endl;
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return -1;
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}
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std::vector<std::string> image_files = {argv[3], argv[4], argv[5]};
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if (std::atoi(argv[6]) == 0) {
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std::cout << "use CpuInfer" << std::endl;
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CpuInfer(argv[1], argv[2], image_files);
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} else if (std::atoi(argv[6]) == 1) {
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GpuInfer(argv[1], argv[2], image_files);
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} else if (std::atoi(argv[6]) == 2) {
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TrtInfer(argv[1], argv[2], image_files);
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} else if (std::atoi(argv[6]) == 3) {
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CpuInfer(argv[1], argv[2], image_files);
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}
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return 0;
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}
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