mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 09:07:10 +08:00
77cb9db6da
* [cmake] add faiss.cmake -> pp-shituv2 * [PP-ShiTuV2] Support PP-ShituV2-Det model * [PP-ShiTuV2] Support PP-ShiTuV2-Det model * [PP-ShiTuV2] Add PPShiTuV2Recognizer c++&python support * [PP-ShiTuV2] Add PPShiTuV2Recognizer c++&python support * [Bug Fix] fix ppshitu_pybind error * [benchmark] Add ppshituv2-det c++ benchmark * [examples] Add PP-ShiTuV2 det & rec examples * [vision] Update vision classification result * [Bug Fix] fix trt shapes setting errors
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 InitAndInfer(const std::string &model_dir, const std::string &image_file,
|
|
const fastdeploy::RuntimeOption &option) {
|
|
auto model_file = model_dir + sep + "inference.pdmodel";
|
|
auto params_file = model_dir + sep + "inference.pdiparams";
|
|
auto config_file = model_dir + sep + "infer_cfg.yml";
|
|
|
|
auto model = fastdeploy::vision::classification::PPShiTuV2Detector(
|
|
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;
|
|
}
|
|
|
|
// print res
|
|
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 path/to/image run_option, "
|
|
"e.g ./infer_demo "
|
|
"./picodet_PPLCNet_x2_5_mainbody_lite_v1.0_infer ./test.jpeg 0"
|
|
<< std::endl;
|
|
return -1;
|
|
}
|
|
|
|
fastdeploy::RuntimeOption option;
|
|
int flag = std::atoi(argv[3]);
|
|
|
|
if (flag == 0) {
|
|
option.UseCpu();
|
|
option.UsePaddleBackend(); // Paddle Inference
|
|
} else if (flag == 1) {
|
|
option.UseCpu();
|
|
option.UseOpenVINOBackend(); // OpenVINO
|
|
} else if (flag == 2) {
|
|
option.UseCpu();
|
|
option.UseOrtBackend(); // ONNX Runtime
|
|
} else if (flag == 3) {
|
|
option.UseCpu();
|
|
option.UseLiteBackend(); // Paddle Lite
|
|
} else if (flag == 4) {
|
|
option.UseGpu();
|
|
option.UsePaddleBackend(); // Paddle Inference
|
|
} else if (flag == 5) {
|
|
option.UseGpu();
|
|
option.UsePaddleInferBackend();
|
|
option.paddle_infer_option.enable_trt = true;
|
|
option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
|
|
{1, 3, 640, 640});
|
|
option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2}, {1, 2});
|
|
option.trt_option.SetShape("im_shape", {1, 2}, {1, 2}, {1, 2});
|
|
} else if (flag == 6) {
|
|
option.UseGpu();
|
|
option.UseOrtBackend(); // ONNX Runtime
|
|
} else if (flag == 7) {
|
|
option.UseGpu();
|
|
option.UseTrtBackend(); // TensorRT
|
|
}
|
|
|
|
std::string model_dir = argv[1];
|
|
std::string image_dir = argv[2];
|
|
InitAndInfer(model_dir, image_dir, option);
|
|
}
|