Files
FastDeploy/fastdeploy/vision/detection/ppdet/ppdet_pybind.cc
Zheng_Bicheng 3e1fc69a0c [Model] Add Picodet RKNPU2 (#635)
* * 更新picodet cpp代码

* * 更新文档
* 更新picodet cpp example

* * 删除无用的debug代码
* 新增python example

* * 修改c++代码

* * 修改python代码

* * 修改postprocess代码

* 修复没有scale_factor导致的bug

* 修复错误

* 更正代码格式

* 更正代码格式
2022-11-21 13:44:34 +08:00

113 lines
5.1 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.
#include "fastdeploy/pybind/main.h"
namespace fastdeploy {
void BindPPDet(pybind11::module& m) {
pybind11::class_<vision::detection::PaddleDetPreprocessor>(
m, "PaddleDetPreprocessor")
.def(pybind11::init<std::string>())
.def("run", [](vision::detection::PaddleDetPreprocessor& self, std::vector<pybind11::array>& im_list) {
std::vector<vision::FDMat> images;
for (size_t i = 0; i < im_list.size(); ++i) {
images.push_back(vision::WrapMat(PyArrayToCvMat(im_list[i])));
}
std::vector<FDTensor> outputs;
if (!self.Run(&images, &outputs)) {
pybind11::eval("raise Exception('Failed to preprocess the input data in PaddleDetPreprocessor.')");
}
for (size_t i = 0; i < outputs.size(); ++i) {
outputs[i].StopSharing();
}
return outputs;
});
pybind11::class_<vision::detection::PaddleDetPostprocessor>(
m, "PaddleDetPostprocessor")
.def(pybind11::init<>())
.def("run", [](vision::detection::PaddleDetPostprocessor& self, std::vector<FDTensor>& inputs) {
std::vector<vision::DetectionResult> results;
if (!self.Run(inputs, &results)) {
pybind11::eval("raise Exception('Failed to postprocess the runtime result in PaddleDetPostprocessor.')");
}
return results;
})
.def("apply_decode_and_nms",
[](vision::detection::PaddleDetPostprocessor& self){
self.ApplyDecodeAndNMS();
})
.def("run", [](vision::detection::PaddleDetPostprocessor& self, std::vector<pybind11::array>& input_array) {
std::vector<vision::DetectionResult> results;
std::vector<FDTensor> inputs;
PyArrayToTensorList(input_array, &inputs, /*share_buffer=*/true);
if (!self.Run(inputs, &results)) {
pybind11::eval("raise Exception('Failed to postprocess the runtime result in PaddleDetPostprocessor.')");
}
return results;
});
pybind11::class_<vision::detection::PPDetBase, FastDeployModel>(m, "PPDetBase")
.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
ModelFormat>())
.def("predict",
[](vision::detection::PPDetBase& self, pybind11::array& data) {
auto mat = PyArrayToCvMat(data);
vision::DetectionResult res;
self.Predict(&mat, &res);
return res;
})
.def("batch_predict",
[](vision::detection::PPDetBase& self, std::vector<pybind11::array>& data) {
std::vector<cv::Mat> images;
for (size_t i = 0; i < data.size(); ++i) {
images.push_back(PyArrayToCvMat(data[i]));
}
std::vector<vision::DetectionResult> results;
self.BatchPredict(images, &results);
return results;
})
.def_property_readonly("preprocessor", &vision::detection::PPDetBase::GetPreprocessor)
.def_property_readonly("postprocessor", &vision::detection::PPDetBase::GetPostprocessor);
pybind11::class_<vision::detection::PPYOLO, vision::detection::PPDetBase>(m, "PPYOLO")
.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
ModelFormat>());
pybind11::class_<vision::detection::PPYOLOE, vision::detection::PPDetBase>(m, "PPYOLOE")
.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
ModelFormat>());
pybind11::class_<vision::detection::PicoDet, vision::detection::PPDetBase>(m, "PicoDet")
.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
ModelFormat>());
pybind11::class_<vision::detection::PaddleYOLOX, vision::detection::PPDetBase>(m, "PaddleYOLOX")
.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
ModelFormat>());
pybind11::class_<vision::detection::FasterRCNN, vision::detection::PPDetBase>(m, "FasterRCNN")
.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
ModelFormat>());
pybind11::class_<vision::detection::YOLOv3, vision::detection::PPDetBase>(m, "YOLOv3")
.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
ModelFormat>());
pybind11::class_<vision::detection::MaskRCNN, vision::detection::PPDetBase>(m, "MaskRCNN")
.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
ModelFormat>());
}
} // namespace fastdeploy