mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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fc71d79e58
* update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * Add YOLOv5Face Model support * fixed examples/vision typos * fixed runtime_option print func bugs
54 lines
1.7 KiB
C++
54 lines
1.7 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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int main() {
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namespace vis = fastdeploy::vision;
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std::string model_file = "../resources/models/yolov5s-face.onnx";
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std::string img_path = "../resources/images/test_face_det.jpg";
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std::string vis_path =
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"../resources/outputs/deepcam_yolov5face_vis_result.jpg";
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auto model = vis::deepcam::YOLOv5Face(model_file);
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if (!model.Initialized()) {
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std::cerr << "Init Failed! Model: " << model_file << std::endl;
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return -1;
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} else {
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std::cout << "Init Done! Model:" << model_file << std::endl;
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}
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model.EnableDebug();
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cv::Mat im = cv::imread(img_path);
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cv::Mat vis_im = im.clone();
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vis::FaceDetectionResult res;
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if (!model.Predict(&im, &res, 0.1f, 0.3f)) {
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std::cerr << "Prediction Failed." << std::endl;
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return -1;
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} else {
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std::cout << "Prediction Done!" << std::endl;
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}
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// 输出预测框结果
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std::cout << res.Str() << std::endl;
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// 可视化预测结果
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vis::Visualize::VisFaceDetection(&vis_im, res, 2, 0.3f);
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cv::imwrite(vis_path, vis_im);
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std::cout << "Detect Done! Saved: " << vis_path << std::endl;
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return 0;
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}
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