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	 beaa0fd190
			
		
	
	beaa0fd190
	
	
	
		
			
			* Add namespace for functions * Refactor PaddleDetection module * finish all the single image test * Update preprocessor.cc * fix some litte detail * add python api * Update postprocessor.cc
		
			
				
	
	
		
			36 lines
		
	
	
		
			1.4 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			36 lines
		
	
	
		
			1.4 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 <pybind11/stl.h>
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| #include "fastdeploy/pybind/main.h"
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| 
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| namespace fastdeploy {
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| void BindPPTinyPosePipeline(pybind11::module& m) {
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|   pybind11::class_<pipeline::PPTinyPose>(m, "PPTinyPose")
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| 
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|       .def(pybind11::init<fastdeploy::vision::detection::PicoDet*,
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|                           fastdeploy::vision::keypointdetection::PPTinyPose*>())
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|       .def("predict", [](pipeline::PPTinyPose& self,
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|                          pybind11::array& data) {
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|         auto mat = PyArrayToCvMat(data);
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|         vision::KeyPointDetectionResult res;
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|         self.Predict(&mat, &res);
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|         return res;
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|       })
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| 
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|       .def_readwrite("detection_model_score_threshold", 
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|                      &pipeline::PPTinyPose::detection_model_score_threshold);
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| }
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| 
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| }  // namespace fastdeploy
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