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https://github.com/PaddlePaddle/FastDeploy.git
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a8458e6729
* Support new model PaddleSeg * Fix conflict * PaddleSeg add visulization function * fix bug * Fix BindPPSeg wrong name * Fix variable name * Update by comments * Add ppseg-unet example python version Co-authored-by: Jason <jiangjiajun@baidu.com>
60 lines
1.9 KiB
C++
60 lines
1.9 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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#include "yaml-cpp/yaml.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/unet_Cityscapes/model.pdmodel";
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std::string params_file =
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"../resources/models/unet_Cityscapes/model.pdiparams";
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std::string config_file = "../resources/models/unet_Cityscapes/deploy.yaml";
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std::string img_path = "../resources/images/cityscapes_demo.png";
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std::string vis_path = "../resources/outputs/vis.jpeg";
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auto model = vis::ppseg::Model(model_file, params_file, config_file);
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if (!model.Initialized()) {
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std::cerr << "Init Failed." << std::endl;
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return -1;
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}
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cv::Mat im = cv::imread(img_path);
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cv::Mat vis_im;
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vis::SegmentationResult 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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} 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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YAML::Node cfg = YAML::LoadFile(config_file);
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int num_classes = 19;
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if (cfg["Deploy"]["num_classes"]) {
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num_classes = cfg["Deploy"]["num_classes"].as<int>();
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}
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// 可视化预测结果
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vis::Visualize::VisSegmentation(im, res, &vis_im, num_classes);
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cv::imwrite(vis_path, vis_im);
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std::cout << "Inference Done! Saved: " << vis_path << std::endl;
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return 0;
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}
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