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https://github.com/PaddlePaddle/FastDeploy.git
synced 2026-05-10 01:21:55 +08:00
DefTruth
58 lines
1.8 KiB
C++
58 lines
1.8 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 = "./modnet_photographic_portrait_matting.onnx";
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std::string img_path = "./matting_1.jpg";
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std::string vis_path = "./vis_result.jpg";
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auto model = vis::zhkkke::MODNet(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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// 设置推理size, 必须和模型文件一致
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model.size = {256, 256};
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cv::Mat im = cv::imread(img_path);
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cv::Mat im_old = im.clone();
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cv::Mat vis_im = im.clone();
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vis::MattingResult res;
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if (!model.Predict(&im, &res)) {
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std::cerr << "Prediction Failed." << std::endl;
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return -1;
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}
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std::cout << "Prediction Done!" << std::endl;
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// 输出预测结果
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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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bool remove_small_connected_area = true;
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vis::Visualize::VisMattingAlpha(im_old, res, &vis_im,
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remove_small_connected_area);
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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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