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infer.cc
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// Copyright (c) 2022 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 "fastdeploy/vision.h"
void CpuInfer(const std::string &model_file, const std::string ¶ms_file,
const std::vector<std::string> &image_file) {
auto option = fastdeploy::RuntimeOption();
auto model = fastdeploy::vision::faceid::AdaFace(model_file, params_file);
if (!model.Initialized()) {
std::cerr << "Failed to initialize." << std::endl;
return;
}
cv::Mat face0 = cv::imread(image_file[0]);
cv::Mat face1 = cv::imread(image_file[1]);
cv::Mat face2 = cv::imread(image_file[2]);
fastdeploy::vision::FaceRecognitionResult res0;
fastdeploy::vision::FaceRecognitionResult res1;
fastdeploy::vision::FaceRecognitionResult res2;
if ((!model.Predict(face0, &res0)) || (!model.Predict(face1, &res1)) ||
(!model.Predict(face2, &res2))) {
std::cerr << "Prediction Failed." << std::endl;
}
std::cout << "Prediction Done!" << std::endl;
std::cout << "--- [Face 0]:" << res0.Str();
std::cout << "--- [Face 1]:" << res1.Str();
std::cout << "--- [Face 2]:" << res2.Str();
float cosine01 = fastdeploy::vision::utils::CosineSimilarity(
res0.embedding, res1.embedding,
model.GetPostprocessor().GetL2Normalize());
float cosine02 = fastdeploy::vision::utils::CosineSimilarity(
res0.embedding, res2.embedding,
model.GetPostprocessor().GetL2Normalize());
std::cout << "Detect Done! Cosine 01: " << cosine01
<< ", Cosine 02:" << cosine02 << std::endl;
}
void KunlunXinInfer(const std::string &model_file, const std::string ¶ms_file,
const std::vector<std::string> &image_file) {
auto option = fastdeploy::RuntimeOption();
option.UseKunlunXin();
auto model = fastdeploy::vision::faceid::AdaFace(model_file, params_file);
if (!model.Initialized()) {
std::cerr << "Failed to initialize." << std::endl;
return;
}
cv::Mat face0 = cv::imread(image_file[0]);
cv::Mat face1 = cv::imread(image_file[1]);
cv::Mat face2 = cv::imread(image_file[2]);
fastdeploy::vision::FaceRecognitionResult res0;
fastdeploy::vision::FaceRecognitionResult res1;
fastdeploy::vision::FaceRecognitionResult res2;
if ((!model.Predict(face0, &res0)) || (!model.Predict(face1, &res1)) ||
(!model.Predict(face2, &res2))) {
std::cerr << "Prediction Failed." << std::endl;
}
std::cout << "Prediction Done!" << std::endl;
std::cout << "--- [Face 0]:" << res0.Str();
std::cout << "--- [Face 1]:" << res1.Str();
std::cout << "--- [Face 2]:" << res2.Str();
float cosine01 = fastdeploy::vision::utils::CosineSimilarity(
res0.embedding, res1.embedding,
model.GetPostprocessor().GetL2Normalize());
float cosine02 = fastdeploy::vision::utils::CosineSimilarity(
res0.embedding, res2.embedding,
model.GetPostprocessor().GetL2Normalize());
std::cout << "Detect Done! Cosine 01: " << cosine01
<< ", Cosine 02:" << cosine02 << std::endl;
}
void GpuInfer(const std::string &model_file, const std::string ¶ms_file,
const std::vector<std::string> &image_file) {
auto option = fastdeploy::RuntimeOption();
option.UseGpu();
auto model =
fastdeploy::vision::faceid::AdaFace(model_file, params_file, option);
if (!model.Initialized()) {
std::cerr << "Failed to initialize." << std::endl;
return;
}
cv::Mat face0 = cv::imread(image_file[0]);
cv::Mat face1 = cv::imread(image_file[1]);
cv::Mat face2 = cv::imread(image_file[2]);
fastdeploy::vision::FaceRecognitionResult res0;
fastdeploy::vision::FaceRecognitionResult res1;
fastdeploy::vision::FaceRecognitionResult res2;
if ((!model.Predict(face0, &res0)) || (!model.Predict(face1, &res1)) ||
(!model.Predict(face2, &res2))) {
std::cerr << "Prediction Failed." << std::endl;
}
std::cout << "Prediction Done!" << std::endl;
std::cout << "--- [Face 0]:" << res0.Str();
std::cout << "--- [Face 1]:" << res1.Str();
std::cout << "--- [Face 2]:" << res2.Str();
float cosine01 = fastdeploy::vision::utils::CosineSimilarity(
res0.embedding, res1.embedding,
model.GetPostprocessor().GetL2Normalize());
float cosine02 = fastdeploy::vision::utils::CosineSimilarity(
res0.embedding, res2.embedding,
model.GetPostprocessor().GetL2Normalize());
std::cout << "Detect Done! Cosine 01: " << cosine01
<< ", Cosine 02:" << cosine02 << std::endl;
}
void TrtInfer(const std::string &model_file, const std::string ¶ms_file,
const std::vector<std::string> &image_file) {
auto option = fastdeploy::RuntimeOption();
option.UseGpu();
option.UseTrtBackend();
option.SetTrtInputShape("data", {1, 3, 112, 112});
auto model =
fastdeploy::vision::faceid::AdaFace(model_file, params_file, option);
if (!model.Initialized()) {
std::cerr << "Failed to initialize." << std::endl;
return;
}
cv::Mat face0 = cv::imread(image_file[0]);
cv::Mat face1 = cv::imread(image_file[1]);
cv::Mat face2 = cv::imread(image_file[2]);
fastdeploy::vision::FaceRecognitionResult res0;
fastdeploy::vision::FaceRecognitionResult res1;
fastdeploy::vision::FaceRecognitionResult res2;
if ((!model.Predict(face0, &res0)) || (!model.Predict(face1, &res1)) ||
(!model.Predict(face2, &res2))) {
std::cerr << "Prediction Failed." << std::endl;
}
std::cout << "Prediction Done!" << std::endl;
std::cout << "--- [Face 0]:" << res0.Str();
std::cout << "--- [Face 1]:" << res1.Str();
std::cout << "--- [Face 2]:" << res2.Str();
float cosine01 = fastdeploy::vision::utils::CosineSimilarity(
res0.embedding, res1.embedding,
model.GetPostprocessor().GetL2Normalize());
float cosine02 = fastdeploy::vision::utils::CosineSimilarity(
res0.embedding, res2.embedding,
model.GetPostprocessor().GetL2Normalize());
std::cout << "Detect Done! Cosine 01: " << cosine01
<< ", Cosine 02:" << cosine02 << std::endl;
}
int main(int argc, char *argv[]) {
if (argc < 7) {
std::cout << "Usage: infer_demo path/to/model path/to/image run_option, "
"e.g ./infer_demo mobilefacenet_adaface.pdmodel "
"mobilefacenet_adaface.pdiparams "
"test_lite_focal_AdaFace_0.JPG test_lite_focal_AdaFace_1.JPG "
"test_lite_focal_AdaFace_2.JPG 0"
<< std::endl;
std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
"with gpu; 2: run with gpu and use tensorrt backend; 3: run with kunlunxin."
<< std::endl;
return -1;
}
std::vector<std::string> image_files = {argv[3], argv[4], argv[5]};
if (std::atoi(argv[6]) == 0) {
std::cout << "use CpuInfer" << std::endl;
CpuInfer(argv[1], argv[2], image_files);
} else if (std::atoi(argv[6]) == 1) {
GpuInfer(argv[1], argv[2], image_files);
} else if (std::atoi(argv[6]) == 2) {
TrtInfer(argv[1], argv[2], image_files);
} else if (std::atoi(argv[6]) == 3) {
KunlunXinInfer(argv[1], argv[2], image_files);
}
return 0;
}