mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-09-28 21:32:29 +08:00
9b108c3fa5
* Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
97 lines
3.2 KiB
C++
97 lines
3.2 KiB
C++
// 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"
|
|
|
|
#ifdef WIN32
|
|
const char sep = '\\';
|
|
#else
|
|
const char sep = '/';
|
|
#endif
|
|
|
|
void CpuInfer(const std::string& model_dir, const std::string& image_file) {
|
|
auto model_file = model_dir + sep + "model.pdmodel";
|
|
auto params_file = model_dir + sep + "model.pdiparams";
|
|
auto config_file = model_dir + sep + "infer_cfg.yml";
|
|
auto option = fastdeploy::RuntimeOption();
|
|
option.UseCpu();
|
|
auto model = fastdeploy::vision::detection::RetinaNet(model_file, params_file,
|
|
config_file, option);
|
|
if (!model.Initialized()) {
|
|
std::cerr << "Failed to initialize." << std::endl;
|
|
return;
|
|
}
|
|
|
|
auto im = cv::imread(image_file);
|
|
|
|
fastdeploy::vision::DetectionResult res;
|
|
if (!model.Predict(im, &res)) {
|
|
std::cerr << "Failed to predict." << std::endl;
|
|
return;
|
|
}
|
|
|
|
std::cout << res.Str() << std::endl;
|
|
auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.5);
|
|
cv::imwrite("vis_result.jpg", vis_im);
|
|
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
|
|
}
|
|
|
|
void GpuInfer(const std::string& model_dir, const std::string& image_file) {
|
|
auto model_file = model_dir + sep + "model.pdmodel";
|
|
auto params_file = model_dir + sep + "model.pdiparams";
|
|
auto config_file = model_dir + sep + "infer_cfg.yml";
|
|
|
|
auto option = fastdeploy::RuntimeOption();
|
|
option.UseGpu();
|
|
auto model = fastdeploy::vision::detection::RetinaNet(model_file, params_file,
|
|
config_file, option);
|
|
if (!model.Initialized()) {
|
|
std::cerr << "Failed to initialize." << std::endl;
|
|
return;
|
|
}
|
|
|
|
auto im = cv::imread(image_file);
|
|
|
|
fastdeploy::vision::DetectionResult res;
|
|
if (!model.Predict(im, &res)) {
|
|
std::cerr << "Failed to predict." << std::endl;
|
|
return;
|
|
}
|
|
|
|
std::cout << res.Str() << std::endl;
|
|
auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.5);
|
|
cv::imwrite("vis_result.jpg", vis_im);
|
|
std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
|
|
}
|
|
|
|
int main(int argc, char* argv[]) {
|
|
if (argc < 4) {
|
|
std::cout
|
|
<< "Usage: infer_demo path/to/model_dir path/to/image run_option, "
|
|
"e.g ./infer_model ./ppyoloe_model_dir ./test.jpeg 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."
|
|
<< std::endl;
|
|
return -1;
|
|
}
|
|
|
|
if (std::atoi(argv[3]) == 0) {
|
|
CpuInfer(argv[1], argv[2]);
|
|
} else if (std::atoi(argv[3]) == 1) {
|
|
GpuInfer(argv[1], argv[2]);
|
|
}
|
|
return 0;
|
|
}
|