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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
		
			
				
	
	
		
			91 lines
		
	
	
		
			3.7 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			91 lines
		
	
	
		
			3.7 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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| 
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| #pragma once
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| #include "fastdeploy/fastdeploy_model.h"
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| #include "fastdeploy/vision/detection/ppdet/preprocessor.h"
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| #include "fastdeploy/vision/detection/ppdet/postprocessor.h"
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| #include "fastdeploy/vision/common/processors/transform.h"
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| #include "fastdeploy/vision/common/result.h"
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| 
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| #include "fastdeploy/vision/utils/utils.h"
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| 
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| namespace fastdeploy {
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| namespace vision {
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| /** \brief All object detection model APIs are defined inside this namespace
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|  *
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|  */
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| namespace detection {
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| 
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| /*! @brief Base model object used when to load a model exported by PaddleDetection
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|  */
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| class FASTDEPLOY_DECL PPDetBase : 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 ppyoloe/model.pdmodel
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|    * \param[in] params_file Path of parameter file, e.g ppyoloe/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 ppyoloe/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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|   PPDetBase(const std::string& model_file, 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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| 
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|   /// Get model's name
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|   virtual std::string ModelName() const { return "PaddleDetection/BaseModel"; }
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| 
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|   /** \brief DEPRECATED Predict the detection result for an input image
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|    *
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|    * \param[in] im The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
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|    * \param[in] result The output detection result
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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* im, DetectionResult* result);
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| 
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|   /** \brief Predict the detection result for an input image
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|    * \param[in] im The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
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|    * \param[in] result The output detection result
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|    * \return true if the prediction successed, otherwise false
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|    */
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|   virtual bool Predict(const cv::Mat& im, DetectionResult* result);
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| 
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|   /** \brief Predict the detection result for an input image list
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|    * \param[in] im The input image list, all the elements come from cv::imread(), is a 3-D array with layout HWC, BGR format
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|    * \param[in] results The output detection result list
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|    * \return true if the prediction successed, otherwise false
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|    */
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|   virtual bool BatchPredict(const std::vector<cv::Mat>& imgs,
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|                             std::vector<DetectionResult>* results);
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| 
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|   PaddleDetPreprocessor& GetPreprocessor() {
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|     return preprocessor_;
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|   }
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| 
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|   PaddleDetPostprocessor& GetPostprocessor() {
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|     return postprocessor_;
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|   }
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| 
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|  protected:
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|   virtual bool Initialize();
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|   PaddleDetPreprocessor preprocessor_;
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|   PaddleDetPostprocessor postprocessor_;
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| };
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| 
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| }  // namespace detection
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| }  // namespace vision
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| }  // namespace fastdeploy
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