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d70b6c99df
* add override mark * delete some * recovery * recovery * add tracking * add tracking py_bind and example * add pptracking * add pptracking * iomanip head file * add opencv_video lib * add python libs package Signed-off-by: ChaoII <849453582@qq.com> * complete comments Signed-off-by: ChaoII <849453582@qq.com> * add jdeTracker_ member variable Signed-off-by: ChaoII <849453582@qq.com> * add 'FASTDEPLOY_DECL' macro Signed-off-by: ChaoII <849453582@qq.com> * remove kwargs params Signed-off-by: ChaoII <849453582@qq.com> * [Doc]update pptracking docs * delete 'ENABLE_PADDLE_FRONTEND' switch * add pptracking unit test * update pptracking unit test Signed-off-by: ChaoII <849453582@qq.com> * modify test video file path and remove trt test * update unit test model url * remove 'FASTDEPLOY_DECL' macro Signed-off-by: ChaoII <849453582@qq.com> * fix build python packages about pptracking on win32 Signed-off-by: ChaoII <849453582@qq.com> * update comment Signed-off-by: ChaoII <849453582@qq.com> * add pptracking model explain Signed-off-by: ChaoII <849453582@qq.com> Signed-off-by: ChaoII <849453582@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com>
80 lines
2.9 KiB
C++
80 lines
2.9 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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#pragma once
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#include "fastdeploy/vision/common/processors/transform.h"
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#include "fastdeploy/fastdeploy_model.h"
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#include "fastdeploy/vision/common/result.h"
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#include "fastdeploy/vision/tracking/pptracking/tracker.h"
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//#include "fastdeploy/vision/tracking/pptracking/letter_box.h"
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namespace fastdeploy {
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namespace vision {
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namespace tracking {
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class FASTDEPLOY_DECL PPTracking: public FastDeployModel {
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public:
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/** \brief Set path of model file and configuration file, and the configuration of runtime
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*
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* \param[in] model_file Path of model file, e.g pptracking/model.pdmodel
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* \param[in] params_file Path of parameter file, e.g pptracking/model.pdiparams, if the model format is ONNX, this parameter will be ignored
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* \param[in] config_file Path of configuration file for deployment, e.g pptracking/infer_cfg.yml
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* \param[in] custom_option RuntimeOption for inference, the default will use cpu, and choose the backend defined in `valid_cpu_backends`
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* \param[in] model_format Model format of the loaded model, default is Paddle format
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*/
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PPTracking(const std::string& model_file,
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const std::string& params_file,
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const std::string& config_file,
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const RuntimeOption& custom_option = RuntimeOption(),
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const ModelFormat& model_format = ModelFormat::PADDLE);
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/// Get model's name
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std::string ModelName() const override { return "pptracking"; }
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/** \brief Predict the detection result for an input image(consecutive)
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*
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* \param[in] im The input image data which is consecutive frame, comes from imread() or videoCapture.read()
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* \param[in] result The output tracking result will be writen to this structure
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* \return true if the prediction successed, otherwise false
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*/
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virtual bool Predict(cv::Mat* img, MOTResult* result);
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private:
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bool BuildPreprocessPipelineFromConfig();
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bool Initialize();
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bool Preprocess(Mat* img, std::vector<FDTensor>* outputs);
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bool Postprocess(std::vector<FDTensor>& infer_result, MOTResult *result);
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std::vector<std::shared_ptr<Processor>> processors_;
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std::string config_file_;
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float draw_threshold_;
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float conf_thresh_;
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float tracked_thresh_;
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float min_box_area_;
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std::unique_ptr<JDETracker> jdeTracker_;
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};
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} // namespace tracking
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} // namespace vision
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} // namespace fastdeploy
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