mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 09:07:10 +08:00
9937b6c325
* Refactor PaddleSeg with preprocessor && postprocessor * Fix bugs * Delete redundancy code * Modify by comments * Refactor according to comments * Add batch evaluation * Add single test script * Add ppliteseg single test script && fix eval(raise) error * fix bug * Fix evaluation segmentation.py batch predict * Fix segmentation evaluation bug * Fix evaluation segmentation bugs * Update segmentation result docs * Update old predict api and DisableNormalizeAndPermute * Update resize segmentation label map with cv::INTER_NEAREST * Add Model Clone function for PaddleClas && PaddleDet && PaddleSeg * Add multi thread demo * Add python model clone function * Add multi thread python && C++ example * Fix bug Co-authored-by: Jason <jiangjiajun@baidu.com>
97 lines
3.9 KiB
C++
97 lines
3.9 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
//
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
#pragma once
|
|
#include "fastdeploy/fastdeploy_model.h"
|
|
#include "fastdeploy/vision/detection/ppdet/preprocessor.h"
|
|
#include "fastdeploy/vision/detection/ppdet/postprocessor.h"
|
|
#include "fastdeploy/vision/common/processors/transform.h"
|
|
#include "fastdeploy/vision/common/result.h"
|
|
|
|
#include "fastdeploy/vision/utils/utils.h"
|
|
|
|
namespace fastdeploy {
|
|
namespace vision {
|
|
/** \brief All object detection model APIs are defined inside this namespace
|
|
*
|
|
*/
|
|
namespace detection {
|
|
|
|
/*! @brief Base model object used when to load a model exported by PaddleDetection
|
|
*/
|
|
class FASTDEPLOY_DECL PPDetBase : public FastDeployModel {
|
|
public:
|
|
/** \brief Set path of model file and configuration file, and the configuration of runtime
|
|
*
|
|
* \param[in] model_file Path of model file, e.g ppyoloe/model.pdmodel
|
|
* \param[in] params_file Path of parameter file, e.g ppyoloe/model.pdiparams, if the model format is ONNX, this parameter will be ignored
|
|
* \param[in] config_file Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
|
|
* \param[in] custom_option RuntimeOption for inference, the default will use cpu, and choose the backend defined in `valid_cpu_backends`
|
|
* \param[in] model_format Model format of the loaded model, default is Paddle format
|
|
*/
|
|
PPDetBase(const std::string& model_file, const std::string& params_file,
|
|
const std::string& config_file,
|
|
const RuntimeOption& custom_option = RuntimeOption(),
|
|
const ModelFormat& model_format = ModelFormat::PADDLE);
|
|
|
|
/** \brief Clone a new PaddleDetModel with less memory usage when multiple instances of the same model are created
|
|
*
|
|
* \return new PaddleDetModel* type unique pointer
|
|
*/
|
|
virtual std::unique_ptr<PPDetBase> Clone() const;
|
|
|
|
/// Get model's name
|
|
virtual std::string ModelName() const { return "PaddleDetection/BaseModel"; }
|
|
|
|
/** \brief DEPRECATED Predict the detection result for an input image
|
|
*
|
|
* \param[in] im The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
|
|
* \param[in] result The output detection result
|
|
* \return true if the prediction successed, otherwise false
|
|
*/
|
|
virtual bool Predict(cv::Mat* im, DetectionResult* result);
|
|
|
|
/** \brief Predict the detection result for an input image
|
|
* \param[in] im The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
|
|
* \param[in] result The output detection result
|
|
* \return true if the prediction successed, otherwise false
|
|
*/
|
|
virtual bool Predict(const cv::Mat& im, DetectionResult* result);
|
|
|
|
/** \brief Predict the detection result for an input image list
|
|
* \param[in] im The input image list, all the elements come from cv::imread(), is a 3-D array with layout HWC, BGR format
|
|
* \param[in] results The output detection result list
|
|
* \return true if the prediction successed, otherwise false
|
|
*/
|
|
virtual bool BatchPredict(const std::vector<cv::Mat>& imgs,
|
|
std::vector<DetectionResult>* results);
|
|
|
|
PaddleDetPreprocessor& GetPreprocessor() {
|
|
return preprocessor_;
|
|
}
|
|
|
|
PaddleDetPostprocessor& GetPostprocessor() {
|
|
return postprocessor_;
|
|
}
|
|
|
|
protected:
|
|
virtual bool Initialize();
|
|
PaddleDetPreprocessor preprocessor_;
|
|
PaddleDetPostprocessor postprocessor_;
|
|
};
|
|
|
|
} // namespace detection
|
|
} // namespace vision
|
|
} // namespace fastdeploy
|