mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-24 17:10:35 +08:00
[CVCUDA] CMake integration, vison processor CV-CUDA integration, PaddleClas support CV-CUDA (#1074)
* cvcuda resize * cvcuda center crop * cvcuda resize * add a fdtensor in fdmat * get cv mat and get tensor support gpu * paddleclas cvcuda preprocessor * fix compile err * fix windows compile error * rename reused to cached * address comment * remove debug code * add comment * add manager run * use cuda and cuda used * use cv cuda doc * address comment --------- Co-authored-by: Jason <jiangjiajun@baidu.com>
This commit is contained in:
Wang Xinyu
@@ -18,76 +18,102 @@ void BindPaddleClas(pybind11::module& m) {
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pybind11::class_<vision::classification::PaddleClasPreprocessor>(
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m, "PaddleClasPreprocessor")
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.def(pybind11::init<std::string>())
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.def("run", [](vision::classification::PaddleClasPreprocessor& self, 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 PaddleClasPreprocessor.");
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}
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if (!self.WithGpu()) {
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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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}
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return outputs;
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})
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.def("use_gpu", [](vision::classification::PaddleClasPreprocessor& self, int gpu_id = -1) {
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self.UseGpu(gpu_id);
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})
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.def("disable_normalize", [](vision::classification::PaddleClasPreprocessor& self) {
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self.DisableNormalize();
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})
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.def("disable_permute", [](vision::classification::PaddleClasPreprocessor& self) {
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self.DisablePermute();
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});
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.def("run",
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[](vision::classification::PaddleClasPreprocessor& 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(
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"Failed to preprocess the input data in "
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"PaddleClasPreprocessor.");
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}
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if (!self.CudaUsed()) {
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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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}
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return outputs;
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})
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.def("use_cuda",
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[](vision::classification::PaddleClasPreprocessor& self,
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bool enable_cv_cuda = false,
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int gpu_id = -1) { self.UseCuda(enable_cv_cuda, gpu_id); })
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.def("disable_normalize",
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[](vision::classification::PaddleClasPreprocessor& self) {
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self.DisableNormalize();
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})
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.def("disable_permute",
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[](vision::classification::PaddleClasPreprocessor& self) {
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self.DisablePermute();
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});
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pybind11::class_<vision::classification::PaddleClasPostprocessor>(
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m, "PaddleClasPostprocessor")
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.def(pybind11::init<int>())
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.def("run", [](vision::classification::PaddleClasPostprocessor& self, std::vector<FDTensor>& inputs) {
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std::vector<vision::ClassifyResult> 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 PaddleClasPostprocessor.");
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}
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return results;
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})
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.def("run", [](vision::classification::PaddleClasPostprocessor& self, std::vector<pybind11::array>& input_array) {
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std::vector<vision::ClassifyResult> 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 PaddleClasPostprocessor.");
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}
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return results;
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})
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.def_property("topk", &vision::classification::PaddleClasPostprocessor::GetTopk, &vision::classification::PaddleClasPostprocessor::SetTopk);
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.def("run",
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[](vision::classification::PaddleClasPostprocessor& self,
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std::vector<FDTensor>& inputs) {
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std::vector<vision::ClassifyResult> results;
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if (!self.Run(inputs, &results)) {
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throw std::runtime_error(
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"Failed to postprocess the runtime result in "
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"PaddleClasPostprocessor.");
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}
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return results;
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})
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.def("run",
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[](vision::classification::PaddleClasPostprocessor& self,
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std::vector<pybind11::array>& input_array) {
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std::vector<vision::ClassifyResult> 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(
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"Failed to postprocess the runtime result in "
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"PaddleClasPostprocessor.");
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}
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return results;
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})
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.def_property("topk",
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&vision::classification::PaddleClasPostprocessor::GetTopk,
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&vision::classification::PaddleClasPostprocessor::SetTopk);
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pybind11::class_<vision::classification::PaddleClasModel, FastDeployModel>(
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m, "PaddleClasModel")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>())
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.def("clone", [](vision::classification::PaddleClasModel& self) {
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return self.Clone();
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})
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.def("predict", [](vision::classification::PaddleClasModel& self, pybind11::array& data) {
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cv::Mat im = PyArrayToCvMat(data);
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vision::ClassifyResult 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::classification::PaddleClasModel& 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::ClassifyResult> 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::classification::PaddleClasModel::GetPreprocessor)
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.def_property_readonly("postprocessor", &vision::classification::PaddleClasModel::GetPostprocessor);
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.def("clone",
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[](vision::classification::PaddleClasModel& self) {
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return self.Clone();
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})
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.def("predict",
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[](vision::classification::PaddleClasModel& self,
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pybind11::array& data) {
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cv::Mat im = PyArrayToCvMat(data);
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vision::ClassifyResult 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",
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[](vision::classification::PaddleClasModel& self,
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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::ClassifyResult> 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(
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"preprocessor",
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&vision::classification::PaddleClasModel::GetPreprocessor)
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.def_property_readonly(
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"postprocessor",
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&vision::classification::PaddleClasModel::GetPostprocessor);
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}
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} // namespace fastdeploy
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