| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899 |
- // 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 "ultra_infer/pybind/main.h"
- namespace ultra_infer {
- void BindPaddleClas(pybind11::module &m) {
- pybind11::class_<vision::classification::PaddleClasPreprocessor,
- vision::ProcessorManager>(m, "PaddleClasPreprocessor")
- .def(pybind11::init<std::string>())
- .def("disable_normalize",
- [](vision::classification::PaddleClasPreprocessor &self) {
- self.DisableNormalize();
- })
- .def("disable_permute",
- [](vision::classification::PaddleClasPreprocessor &self) {
- self.DisablePermute();
- })
- .def("initial_resize_on_cpu",
- [](vision::classification::PaddleClasPreprocessor &self, bool v) {
- self.InitialResizeOnCpu(v);
- });
- pybind11::class_<vision::classification::PaddleClasPostprocessor>(
- m, "PaddleClasPostprocessor")
- .def(pybind11::init<int>())
- .def("run",
- [](vision::classification::PaddleClasPostprocessor &self,
- std::vector<FDTensor> &inputs) {
- std::vector<vision::ClassifyResult> results;
- if (!self.Run(inputs, &results)) {
- throw std::runtime_error(
- "Failed to postprocess the runtime result in "
- "PaddleClasPostprocessor.");
- }
- return results;
- })
- .def("run",
- [](vision::classification::PaddleClasPostprocessor &self,
- std::vector<pybind11::array> &input_array) {
- std::vector<vision::ClassifyResult> results;
- std::vector<FDTensor> inputs;
- PyArrayToTensorList(input_array, &inputs, /*share_buffer=*/true);
- if (!self.Run(inputs, &results)) {
- throw std::runtime_error(
- "Failed to postprocess the runtime result in "
- "PaddleClasPostprocessor.");
- }
- return results;
- })
- .def_property("topk",
- &vision::classification::PaddleClasPostprocessor::GetTopk,
- &vision::classification::PaddleClasPostprocessor::SetTopk);
- pybind11::class_<vision::classification::PaddleClasModel, UltraInferModel>(
- m, "PaddleClasModel")
- .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
- ModelFormat>())
- .def("clone",
- [](vision::classification::PaddleClasModel &self) {
- return self.Clone();
- })
- .def("predict",
- [](vision::classification::PaddleClasModel &self,
- pybind11::array &data) {
- cv::Mat im = PyArrayToCvMat(data);
- vision::ClassifyResult result;
- self.Predict(im, &result);
- return result;
- })
- .def("batch_predict",
- [](vision::classification::PaddleClasModel &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::ClassifyResult> results;
- self.BatchPredict(images, &results);
- return results;
- })
- .def_property_readonly(
- "preprocessor",
- &vision::classification::PaddleClasModel::GetPreprocessor)
- .def_property_readonly(
- "postprocessor",
- &vision::classification::PaddleClasModel::GetPostprocessor);
- }
- } // namespace ultra_infer
|