mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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* first draft * add robx iou * add benchmark for ppyoloe_r * remove trash code * fix bugs * add pybind nms rotated option * add missing head file * fix bug * fix bug2 * fix shape bug --------- Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
264 lines
12 KiB
C++
264 lines
12 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 BindPPDet(pybind11::module& m) {
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pybind11::class_<vision::detection::PaddleDetPreprocessor,
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vision::ProcessorManager>(m, "PaddleDetPreprocessor")
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.def(pybind11::init<std::string>())
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.def("run",
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[](vision::detection::PaddleDetPreprocessor& 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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"PaddleDetPreprocessor.");
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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("disable_normalize",
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[](vision::detection::PaddleDetPreprocessor& self) {
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self.DisableNormalize();
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})
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.def("disable_permute",
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[](vision::detection::PaddleDetPreprocessor& self) {
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self.DisablePermute();
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});
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pybind11::class_<vision::detection::NMSOption>(m, "NMSOption")
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.def(pybind11::init())
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.def_readwrite("background_label",
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&vision::detection::NMSOption::background_label)
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.def_readwrite("keep_top_k", &vision::detection::NMSOption::keep_top_k)
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.def_readwrite("nms_eta", &vision::detection::NMSOption::nms_eta)
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.def_readwrite("nms_threshold",
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&vision::detection::NMSOption::nms_threshold)
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.def_readwrite("nms_top_k", &vision::detection::NMSOption::nms_top_k)
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.def_readwrite("normalized", &vision::detection::NMSOption::normalized)
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.def_readwrite("score_threshold",
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&vision::detection::NMSOption::score_threshold);
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pybind11::class_<vision::detection::PaddleDetPostprocessor>(
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m, "PaddleDetPostprocessor")
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.def(pybind11::init<>())
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.def(pybind11::init<std::string>())
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.def("run",
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[](vision::detection::PaddleDetPostprocessor& self,
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std::vector<FDTensor>& inputs) {
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std::vector<vision::DetectionResult> 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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"PaddleDetPostprocessor.");
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}
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return results;
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})
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.def("set_nms_option",
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[](vision::detection::PaddleDetPostprocessor& self,
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vision::detection::NMSOption option) {
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self.SetNMSOption(option);
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})
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.def("set_nms_rotated_option",
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[](vision::detection::PaddleDetPostprocessor& self,
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vision::detection::NMSRotatedOption option) {
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self.SetNMSRotatedOption(option);
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})
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.def("apply_nms",
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[](vision::detection::PaddleDetPostprocessor& self) {
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self.ApplyNMS();
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})
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.def("run", [](vision::detection::PaddleDetPostprocessor& self,
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std::vector<pybind11::array>& input_array) {
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std::vector<vision::DetectionResult> 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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"PaddleDetPostprocessor.");
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}
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return results;
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});
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pybind11::class_<vision::detection::PPDetBase, FastDeployModel>(m,
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"PPDetBase")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>())
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.def("predict",
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[](vision::detection::PPDetBase& self, pybind11::array& data) {
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auto mat = PyArrayToCvMat(data);
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vision::DetectionResult res;
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self.Predict(&mat, &res);
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return res;
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})
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.def("batch_predict",
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[](vision::detection::PPDetBase& 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::DetectionResult> results;
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self.BatchPredict(images, &results);
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return results;
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})
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.def("clone",
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[](vision::detection::PPDetBase& self) { return self.Clone(); })
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.def_property_readonly("preprocessor",
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&vision::detection::PPDetBase::GetPreprocessor)
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.def_property_readonly("postprocessor",
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&vision::detection::PPDetBase::GetPostprocessor);
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pybind11::class_<vision::detection::PPYOLO, vision::detection::PPDetBase>(
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m, "PPYOLO")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PPYOLOE, vision::detection::PPDetBase>(
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m, "PPYOLOE")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PicoDet, vision::detection::PPDetBase>(
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m, "PicoDet")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PaddleYOLOX,
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vision::detection::PPDetBase>(m, "PaddleYOLOX")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::FasterRCNN, vision::detection::PPDetBase>(
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m, "FasterRCNN")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::YOLOv3, vision::detection::PPDetBase>(
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m, "YOLOv3")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::MaskRCNN, vision::detection::PPDetBase>(
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m, "MaskRCNN")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::SSD, vision::detection::PPDetBase>(m,
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"SSD")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PaddleYOLOv5,
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vision::detection::PPDetBase>(m, "PaddleYOLOv5")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PaddleYOLOv6,
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vision::detection::PPDetBase>(m, "PaddleYOLOv6")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PaddleYOLOv7,
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vision::detection::PPDetBase>(m, "PaddleYOLOv7")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PaddleYOLOv8,
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vision::detection::PPDetBase>(m, "PaddleYOLOv8")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::RTMDet, vision::detection::PPDetBase>(
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m, "RTMDet")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::CascadeRCNN,
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vision::detection::PPDetBase>(m, "CascadeRCNN")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PSSDet, vision::detection::PPDetBase>(
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m, "PSSDet")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::RetinaNet, vision::detection::PPDetBase>(
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m, "RetinaNet")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PPYOLOESOD, vision::detection::PPDetBase>(
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m, "PPYOLOESOD")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::FCOS, vision::detection::PPDetBase>(
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m, "FCOS")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::TTFNet, vision::detection::PPDetBase>(
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m, "TTFNet")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::TOOD, vision::detection::PPDetBase>(
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m, "TOOD")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::GFL, vision::detection::PPDetBase>(m,
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"GFL")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::SOLOv2, vision::detection::PPDetBase>(
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m, "SOLOv2")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::PPYOLOER, vision::detection::PPDetBase>(
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m, "PPYOLOER")
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.def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
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ModelFormat>());
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pybind11::class_<vision::detection::NMSRotatedOption>(m, "NMSRotatedOption")
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.def(pybind11::init())
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.def_readwrite("background_label",
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&vision::detection::NMSRotatedOption::background_label)
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.def_readwrite("keep_top_k",
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&vision::detection::NMSRotatedOption::keep_top_k)
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.def_readwrite("nms_eta", &vision::detection::NMSRotatedOption::nms_eta)
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.def_readwrite("nms_threshold",
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&vision::detection::NMSRotatedOption::nms_threshold)
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.def_readwrite("nms_top_k",
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&vision::detection::NMSRotatedOption::nms_top_k)
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.def_readwrite("normalized",
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&vision::detection::NMSRotatedOption::normalized)
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.def_readwrite("score_threshold",
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&vision::detection::NMSRotatedOption::score_threshold);
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}
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} // namespace fastdeploy
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