103 lines
4.2 KiB
C++
103 lines
4.2 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/common/processors/transform.h"
|
|
#include "fastdeploy/vision/common/result.h"
|
|
|
|
namespace fastdeploy {
|
|
|
|
namespace vision {
|
|
|
|
namespace detection {
|
|
/*! @brief YOLOX model object used when to load a YOLOX model exported by YOLOX.
|
|
*/
|
|
class FASTDEPLOY_DECL YOLOX : public FastDeployModel {
|
|
public:
|
|
/** \brief Set path of model file and the configuration of runtime.
|
|
*
|
|
* \param[in] model_file Path of model file, e.g ./yolox.onnx
|
|
* \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] 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 ONNX format
|
|
*/
|
|
YOLOX(const std::string& model_file, const std::string& params_file = "",
|
|
const RuntimeOption& custom_option = RuntimeOption(),
|
|
const ModelFormat& model_format = ModelFormat::ONNX);
|
|
|
|
std::string ModelName() const { return "YOLOX"; }
|
|
/** \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 will be writen to this structure
|
|
* \param[in] conf_threshold confidence threashold for postprocessing, default is 0.25
|
|
* \param[in] nms_iou_threshold iou threashold for NMS, default is 0.5
|
|
* \return true if the prediction successed, otherwise false
|
|
*/
|
|
virtual bool Predict(cv::Mat* im, DetectionResult* result,
|
|
float conf_threshold = 0.25,
|
|
float nms_iou_threshold = 0.5);
|
|
|
|
/*! @brief
|
|
Argument for image preprocessing step, tuple of (width, height), decide the target size after resize, default size = {640, 640}
|
|
*/
|
|
std::vector<int> size;
|
|
// padding value, size should be the same as channels
|
|
std::vector<float> padding_value;
|
|
/*! @brief
|
|
whether the model_file was exported with decode module. The official
|
|
YOLOX/tools/export_onnx.py script will export ONNX file without
|
|
decode module. Please set it 'true' manually if the model file
|
|
was exported with decode module. default false.
|
|
*/
|
|
bool is_decode_exported;
|
|
// downsample strides for YOLOX to generate anchors,
|
|
// will take (8,16,32) as default values, might have stride=64
|
|
std::vector<int> downsample_strides;
|
|
// for offseting the boxes by classes when using NMS, default 4096
|
|
float max_wh;
|
|
|
|
private:
|
|
bool Initialize();
|
|
|
|
bool Preprocess(Mat* mat, FDTensor* outputs,
|
|
std::map<std::string, std::array<float, 2>>* im_info);
|
|
|
|
bool Postprocess(FDTensor& infer_result, DetectionResult* result,
|
|
const std::map<std::string, std::array<float, 2>>& im_info,
|
|
float conf_threshold, float nms_iou_threshold);
|
|
|
|
bool PostprocessWithDecode(
|
|
FDTensor& infer_result, DetectionResult* result,
|
|
const std::map<std::string, std::array<float, 2>>& im_info,
|
|
float conf_threshold, float nms_iou_threshold);
|
|
|
|
bool IsDynamicInput() const { return is_dynamic_input_; }
|
|
|
|
// whether to inference with dynamic shape (e.g ONNX export with dynamic shape
|
|
// or not.)
|
|
// megvii/YOLOX official 'export_onnx.py' script will export static ONNX by
|
|
// default.
|
|
// while is_dynamic_shape if 'false', is_mini_pad will force 'false'. This
|
|
// value will
|
|
// auto check by fastdeploy after the internal Runtime already initialized.
|
|
bool is_dynamic_input_;
|
|
};
|
|
|
|
} // namespace detection
|
|
} // namespace vision
|
|
} // namespace fastdeploy
|