// 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 { namespace vision { // PyProcessorManager is used for pybind11::init() of ProcessorManager // Because ProcessorManager have a pure Virtual function Apply() class FASTDEPLOY_DECL PyProcessorManager : public ProcessorManager { public: using ProcessorManager::ProcessorManager; bool Apply(FDMatBatch* image_batch, std::vector* outputs) override { PYBIND11_OVERRIDE_PURE(bool, ProcessorManager, Apply, image_batch, outputs); } }; } // namespace vision void BindProcessorManager(pybind11::module& m) { pybind11::class_( m, "ProcessorManager") .def(pybind11::init<>()) .def("run", [](vision::ProcessorManager& self, std::vector& im_list) { std::vector images; for (size_t i = 0; i < im_list.size(); ++i) { images.push_back(vision::WrapMat(PyArrayToCvMat(im_list[i]))); } std::vector outputs; if (!self.Run(&images, &outputs)) { throw std::runtime_error("Failed to process the input data"); } if (!self.CudaUsed()) { for (size_t i = 0; i < outputs.size(); ++i) { outputs[i].StopSharing(); } } return outputs; }) .def("pre_apply", &vision::ProcessorManager::PreApply) .def("post_apply", &vision::ProcessorManager::PostApply) .def("use_cuda", [](vision::ProcessorManager& self, bool enable_cv_cuda = false, int gpu_id = -1) { self.UseCuda(enable_cv_cuda, gpu_id); }); } } // namespace fastdeploy