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ec67f8ee6d
* 重构insightface代码 * 重写insightface example代码 * 重写insightface example代码 * 删除多余代码 * 修改预处理代码 * 修改文档 * 修改文档 * 恢复误删除的文件 * 修改cpp example * 修改cpp example * 测试python代码 * 测试python代码 * 测试python代码 * 测试python代码 * 测试python代码 * 测试python代码 * 测试python代码 * 跑通python代码 * 修复重复初始化的bug * 更新adaface的python代码 * 修复c++重复初始化的问题 * 修复c++重复初始化的问题 * 修复Python重复初始化的问题 * 新增preprocess的几个参数的获取方式 * 修复注释的错误 * 按照要求修改 * 修改文档中的图片为图片压缩包 * 修改编译完成后程序的提示 * 更新错误include * 删除无用文件 * 更新文档
90 lines
4.1 KiB
C++
90 lines
4.1 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "fastdeploy/pybind/main.h"
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namespace fastdeploy {
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void BindAdaFace(pybind11::module& m) {
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pybind11::class_<vision::faceid::AdaFacePreprocessor>(
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m, "AdaFacePreprocessor")
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.def(pybind11::init())
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.def("run", [](vision::faceid::AdaFacePreprocessor& self,
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std::vector<pybind11::array>& im_list) {
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std::vector<vision::FDMat> images;
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for (size_t i = 0; i < im_list.size(); ++i) {
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images.push_back(vision::WrapMat(PyArrayToCvMat(im_list[i])));
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}
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std::vector<FDTensor> outputs;
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if (!self.Run(&images, &outputs)) {
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throw std::runtime_error("Failed to preprocess the input data in AdaFacePreprocessor.");
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}
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for (size_t i = 0; i < outputs.size(); ++i) {
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outputs[i].StopSharing();
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}
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return outputs;
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})
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.def_property("permute", &vision::faceid::AdaFacePreprocessor::GetPermute,
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&vision::faceid::AdaFacePreprocessor::SetPermute)
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.def_property("alpha", &vision::faceid::AdaFacePreprocessor::GetAlpha,
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&vision::faceid::AdaFacePreprocessor::SetAlpha)
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.def_property("beta", &vision::faceid::AdaFacePreprocessor::GetBeta,
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&vision::faceid::AdaFacePreprocessor::SetBeta)
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.def_property("size", &vision::faceid::AdaFacePreprocessor::GetSize,
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&vision::faceid::AdaFacePreprocessor::SetSize);
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pybind11::class_<vision::faceid::AdaFacePostprocessor>(
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m, "AdaFacePostprocessor")
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.def(pybind11::init())
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.def("run", [](vision::faceid::AdaFacePostprocessor& self, std::vector<FDTensor>& inputs) {
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std::vector<vision::FaceRecognitionResult> results;
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if (!self.Run(inputs, &results)) {
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throw std::runtime_error("Failed to postprocess the runtime result in AdaFacePostprocessor.");
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}
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return results;
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})
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.def("run", [](vision::faceid::AdaFacePostprocessor& self, std::vector<pybind11::array>& input_array) {
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std::vector<vision::FaceRecognitionResult> results;
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std::vector<FDTensor> inputs;
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PyArrayToTensorList(input_array, &inputs, /*share_buffer=*/true);
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if (!self.Run(inputs, &results)) {
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throw std::runtime_error("Failed to postprocess the runtime result in AdaFacePostprocessor.");
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}
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return results;
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})
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.def_property("l2_normalize", &vision::faceid::AdaFacePostprocessor::GetL2Normalize,
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&vision::faceid::AdaFacePostprocessor::SetL2Normalize);
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pybind11::class_<vision::faceid::AdaFace, FastDeployModel>(
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m, "AdaFace")
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.def(pybind11::init<std::string, std::string, RuntimeOption, ModelFormat>())
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.def("predict", [](vision::faceid::AdaFace& self, pybind11::array& data) {
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cv::Mat im = PyArrayToCvMat(data);
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vision::FaceRecognitionResult result;
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self.Predict(im, &result);
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return result;
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})
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.def("batch_predict", [](vision::faceid::AdaFace& self, std::vector<pybind11::array>& data) {
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std::vector<cv::Mat> images;
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for (size_t i = 0; i < data.size(); ++i) {
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images.push_back(PyArrayToCvMat(data[i]));
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}
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std::vector<vision::FaceRecognitionResult> results;
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self.BatchPredict(images, &results);
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return results;
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})
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.def_property_readonly("preprocessor", &vision::faceid::AdaFace::GetPreprocessor)
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.def_property_readonly("postprocessor", &vision::faceid::AdaFace::GetPostprocessor);
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}
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} // namespace fastdeploy
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