Files
FastDeploy/fastdeploy/vision/facedet/contrib/centerface/centerface_pybind.cc
guxukai 1c115bb237 [Model] Add facedet model: CenterFace (#1131)
* cpp example run success

* add landmarks

* fix reviewed problem

* add pybind

* add readme in examples

* fix reviewed problem

* new file:   tests/models/test_centerface.py

* fix reviewed problem 230202
2023-02-07 14:05:08 +08:00

86 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.
#include "fastdeploy/pybind/main.h"
namespace fastdeploy {
void BindCenterFace(pybind11::module& m) {
pybind11::class_<vision::facedet::CenterFacePreprocessor>(
m, "CenterFacePreprocessor")
.def(pybind11::init<>())
.def("run", [](vision::facedet::CenterFacePreprocessor& 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;
std::vector<std::map<std::string, std::array<float, 2>>> ims_info;
if (!self.Run(&images, &outputs, &ims_info)) {
throw std::runtime_error("Failed to preprocess the input data in CenterFacePreprocessor.");
}
for (size_t i = 0; i < outputs.size(); ++i) {
outputs[i].StopSharing();
}
return make_pair(outputs, ims_info);
})
.def_property("size", &vision::facedet::CenterFacePreprocessor::GetSize, &vision::facedet::CenterFacePreprocessor::SetSize);
pybind11::class_<vision::facedet::CenterFacePostprocessor>(
m, "CenterFacePostprocessor")
.def(pybind11::init<>())
.def("run", [](vision::facedet::CenterFacePostprocessor& self, std::vector<FDTensor>& inputs,
const std::vector<std::map<std::string, std::array<float, 2>>>& ims_info) {
std::vector<vision::FaceDetectionResult> results;
if (!self.Run(inputs, &results, ims_info)) {
throw std::runtime_error("Failed to postprocess the runtime result in CenterFacePostprocessor.");
}
return results;
})
.def("run", [](vision::facedet::CenterFacePostprocessor& self, std::vector<pybind11::array>& input_array,
const std::vector<std::map<std::string, std::array<float, 2>>>& ims_info) {
std::vector<vision::FaceDetectionResult> results;
std::vector<FDTensor> inputs;
PyArrayToTensorList(input_array, &inputs, /*share_buffer=*/true);
if (!self.Run(inputs, &results, ims_info)) {
throw std::runtime_error("Failed to postprocess the runtime result in CenterFacePostprocessor.");
}
return results;
})
.def_property("conf_threshold", &vision::facedet::CenterFacePostprocessor::GetConfThreshold, &vision::facedet::CenterFacePostprocessor::SetConfThreshold)
.def_property("nms_threshold", &vision::facedet::CenterFacePostprocessor::GetNMSThreshold, &vision::facedet::CenterFacePostprocessor::SetNMSThreshold);
pybind11::class_<vision::facedet::CenterFace, FastDeployModel>(m, "CenterFace")
.def(pybind11::init<std::string, std::string, RuntimeOption,
ModelFormat>())
.def("predict",
[](vision::facedet::CenterFace& self, pybind11::array& data) {
auto mat = PyArrayToCvMat(data);
vision::FaceDetectionResult res;
self.Predict(mat, &res);
return res;
})
.def("batch_predict", [](vision::facedet::CenterFace& 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::FaceDetectionResult> results;
self.BatchPredict(images, &results);
return results;
})
.def_property_readonly("preprocessor", &vision::facedet::CenterFace::GetPreprocessor)
.def_property_readonly("postprocessor", &vision::facedet::CenterFace::GetPostprocessor);
}
} // namespace fastdeploy