mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 17:17:14 +08:00
110 lines
5.0 KiB
C++
110 lines
5.0 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 BindPPSeg(pybind11::module& m) {
|
|
pybind11::class_<vision::segmentation::PaddleSegPreprocessor>(
|
|
m, "PaddleSegPreprocessor")
|
|
.def(pybind11::init<std::string>())
|
|
.def("run",
|
|
[](vision::segmentation::PaddleSegPreprocessor& 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])));
|
|
}
|
|
// Record the shape of input images
|
|
std::map<std::string, std::vector<std::array<int, 2>>> imgs_info;
|
|
std::vector<FDTensor> outputs;
|
|
if (!self.Run(&images, &outputs, &imgs_info)) {
|
|
throw std::runtime_error("Failed to preprocess the input data in PaddleSegPreprocessor.");
|
|
}
|
|
for (size_t i = 0; i < outputs.size(); ++i) {
|
|
outputs[i].StopSharing();
|
|
}
|
|
return make_pair(outputs, imgs_info);;
|
|
})
|
|
.def("disable_normalize", [](vision::segmentation::PaddleSegPreprocessor& self) {
|
|
self.DisableNormalize();
|
|
})
|
|
.def("disable_permute", [](vision::segmentation::PaddleSegPreprocessor& self) {
|
|
self.DisablePermute();
|
|
})
|
|
.def_property("is_vertical_screen",
|
|
&vision::segmentation::PaddleSegPreprocessor::GetIsVerticalScreen,
|
|
&vision::segmentation::PaddleSegPreprocessor::SetIsVerticalScreen);
|
|
|
|
pybind11::class_<vision::segmentation::PaddleSegModel, FastDeployModel>(
|
|
m, "PaddleSegModel")
|
|
.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
|
|
ModelFormat>())
|
|
.def("clone", [](vision::segmentation::PaddleSegModel& self) {
|
|
return self.Clone();
|
|
})
|
|
.def("predict",
|
|
[](vision::segmentation::PaddleSegModel& self,
|
|
pybind11::array& data) {
|
|
auto mat = PyArrayToCvMat(data);
|
|
vision::SegmentationResult res;
|
|
self.Predict(&mat, &res);
|
|
return res;
|
|
})
|
|
.def("batch_predict",
|
|
[](vision::segmentation::PaddleSegModel& 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::SegmentationResult> results;
|
|
self.BatchPredict(images, &results);
|
|
return results;
|
|
})
|
|
.def_property_readonly("preprocessor", &vision::segmentation::PaddleSegModel::GetPreprocessor)
|
|
.def_property_readonly("postprocessor", &vision::segmentation::PaddleSegModel::GetPostprocessor);
|
|
|
|
pybind11::class_<vision::segmentation::PaddleSegPostprocessor>(
|
|
m, "PaddleSegPostprocessor")
|
|
.def(pybind11::init<std::string>())
|
|
.def("run",
|
|
[](vision::segmentation::PaddleSegPostprocessor& self,
|
|
std::vector<FDTensor>& inputs,
|
|
const std::map<std::string, std::vector<std::array<int, 2>>>& imgs_info) {
|
|
std::vector<vision::SegmentationResult> results;
|
|
if (!self.Run(inputs, &results, imgs_info)) {
|
|
throw std::runtime_error("Failed to postprocess the runtime result in PaddleSegPostprocessor.");
|
|
}
|
|
return results;
|
|
})
|
|
.def("run",
|
|
[](vision::segmentation::PaddleSegPostprocessor& self,
|
|
std::vector<pybind11::array>& input_array,
|
|
const std::map<std::string, std::vector<std::array<int, 2>>>& imgs_info) {
|
|
std::vector<vision::SegmentationResult> results;
|
|
std::vector<FDTensor> inputs;
|
|
PyArrayToTensorList(input_array, &inputs, /*share_buffer=*/true);
|
|
if (!self.Run(inputs, &results, imgs_info)) {
|
|
throw std::runtime_error("Failed to postprocess the runtime result in PaddleSegPostprocessor.");
|
|
}
|
|
return results;
|
|
})
|
|
.def_property("apply_softmax",
|
|
&vision::segmentation::PaddleSegPostprocessor::GetApplySoftmax,
|
|
&vision::segmentation::PaddleSegPostprocessor::SetApplySoftmax)
|
|
.def_property("store_score_map",
|
|
&vision::segmentation::PaddleSegPostprocessor::GetStoreScoreMap,
|
|
&vision::segmentation::PaddleSegPostprocessor::SetStoreScoreMap);
|
|
}
|
|
} // namespace fastdeploy
|