Files
FastDeploy/fastdeploy/vision/detection/ppdet/model.h
Zheng-Bicheng 0687d3b0ad [Model] Add Solov2 For PaddleDetection (#1435)
* update solov2

* Repair note

* update solov2 postprocess

* update

* update solov2

* update solov2

* fixed bug

* fixed bug

* update solov2

* update solov2

* fix build android bug

* update docs

* update docs

* update docs

* update

* update

* update arch and docs

* update

* update

* update solov2 python

---------

Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
2023-03-08 10:01:32 +08:00

444 lines
19 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/vision/detection/ppdet/base.h"
#include "fastdeploy/vision/detection/ppdet/multiclass_nms.h"
namespace fastdeploy {
namespace vision {
namespace detection {
class FASTDEPLOY_DECL PicoDet : public PPDetBase {
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 picodet/model.pdmodel
* \param[in] params_file Path of parameter file, e.g picodet/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 picodet/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
*/
PicoDet(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER,
Backend::LITE};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_rknpu_backends = {Backend::RKNPU2};
valid_kunlunxin_backends = {Backend::LITE};
valid_ascend_backends = {Backend::LITE};
valid_sophgonpu_backends = {Backend::SOPHGOTPU};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PicoDet"; }
};
class FASTDEPLOY_DECL SOLOv2 : public PPDetBase {
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 picodet/model.pdmodel
* \param[in] params_file Path of parameter file, e.g picodet/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 picodet/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
*/
SOLOv2(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = { Backend::PDINFER};
valid_gpu_backends = {Backend::PDINFER, Backend::TRT};
initialized = Initialize();
}
virtual std::string ModelName() const { return "SOLOv2"; }
};
class FASTDEPLOY_DECL PPYOLOE : public PPDetBase {
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 picodet/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 picodet/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
*/
PPYOLOE(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER,
Backend::LITE};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_timvx_backends = {Backend::LITE};
valid_kunlunxin_backends = {Backend::LITE};
valid_rknpu_backends = {Backend::RKNPU2};
valid_ascend_backends = {Backend::LITE};
valid_sophgonpu_backends = {Backend::SOPHGOTPU};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PPYOLOE"; }
};
class FASTDEPLOY_DECL PPYOLO : public PPDetBase {
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 ppyolo/model.pdmodel
* \param[in] params_file Path of parameter file, e.g ppyolo/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 picodet/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
*/
PPYOLO(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER, Backend::LITE};
valid_gpu_backends = {Backend::PDINFER};
valid_kunlunxin_backends = {Backend::LITE};
valid_ascend_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/PP-YOLO"; }
};
class FASTDEPLOY_DECL YOLOv3 : public PPDetBase {
public:
YOLOv3(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER,
Backend::LITE};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_kunlunxin_backends = {Backend::LITE};
valid_ascend_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/YOLOv3"; }
};
class FASTDEPLOY_DECL PaddleYOLOX : public PPDetBase {
public:
PaddleYOLOX(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER,
Backend::LITE};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_kunlunxin_backends = {Backend::LITE};
valid_ascend_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/YOLOX"; }
};
class FASTDEPLOY_DECL FasterRCNN : public PPDetBase {
public:
FasterRCNN(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER, Backend::LITE};
valid_gpu_backends = {Backend::PDINFER};
valid_kunlunxin_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/FasterRCNN"; }
};
class FASTDEPLOY_DECL MaskRCNN : public PPDetBase {
public:
MaskRCNN(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER, Backend::LITE};
valid_gpu_backends = {Backend::PDINFER};
valid_kunlunxin_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/MaskRCNN"; }
};
class FASTDEPLOY_DECL SSD : public PPDetBase {
public:
SSD(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER, Backend::LITE};
valid_gpu_backends = {Backend::PDINFER};
valid_kunlunxin_backends = {Backend::LITE};
valid_ascend_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/SSD"; }
};
class FASTDEPLOY_DECL PaddleYOLOv5 : public PPDetBase {
public:
PaddleYOLOv5(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::ORT, Backend::PDINFER};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_kunlunxin_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/YOLOv5"; }
};
class FASTDEPLOY_DECL PaddleYOLOv6 : public PPDetBase {
public:
PaddleYOLOv6(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_kunlunxin_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/YOLOv6"; }
};
class FASTDEPLOY_DECL PaddleYOLOv7 : public PPDetBase {
public:
PaddleYOLOv7(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::ORT, Backend::PDINFER};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_kunlunxin_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/YOLOv7"; }
};
class FASTDEPLOY_DECL PaddleYOLOv8 : public PPDetBase {
public:
PaddleYOLOv8(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER,
Backend::LITE};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_kunlunxin_backends = {Backend::LITE};
valid_rknpu_backends = {Backend::RKNPU2};
valid_ascend_backends = {Backend::LITE};
valid_sophgonpu_backends = {Backend::SOPHGOTPU};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/YOLOv8"; }
};
class FASTDEPLOY_DECL RTMDet : public PPDetBase {
public:
RTMDet(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_kunlunxin_backends = {Backend::LITE};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/RTMDet"; }
};
class FASTDEPLOY_DECL CascadeRCNN : public PPDetBase {
public:
CascadeRCNN(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER};
valid_gpu_backends = {Backend::PDINFER};
initialized = Initialize();
}
virtual std::string ModelName() const {
return "PaddleDetection/CascadeRCNN";
}
};
class FASTDEPLOY_DECL PSSDet : public PPDetBase {
public:
PSSDet(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER};
valid_gpu_backends = {Backend::PDINFER};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/PSSDet"; }
};
class FASTDEPLOY_DECL RetinaNet : public PPDetBase {
public:
RetinaNet(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER};
valid_gpu_backends = {Backend::PDINFER};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/RetinaNet"; }
};
class FASTDEPLOY_DECL PPYOLOESOD : public PPDetBase {
public:
PPYOLOESOD(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::ORT, Backend::PDINFER};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/PPYOLOESOD"; }
};
class FASTDEPLOY_DECL FCOS : public PPDetBase {
public:
FCOS(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/FCOS"; }
};
class FASTDEPLOY_DECL TTFNet : public PPDetBase {
public:
TTFNet(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER};
valid_gpu_backends = {Backend::PDINFER};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/TTFNet"; }
};
class FASTDEPLOY_DECL TOOD : public PPDetBase {
public:
TOOD(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::PDINFER};
valid_gpu_backends = {Backend::PDINFER};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/TOOD"; }
};
class FASTDEPLOY_DECL GFL : public PPDetBase {
public:
GFL(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)
: PPDetBase(model_file, params_file, config_file, custom_option,
model_format) {
valid_cpu_backends = {Backend::ORT, Backend::PDINFER};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER};
initialized = Initialize();
}
virtual std::string ModelName() const { return "PaddleDetection/GFL"; }
};
} // namespace detection
} // namespace vision
} // namespace fastdeploy