mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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109 lines
4.4 KiB
C++
109 lines
4.4 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::PPYOLOE, FastDeployModel>(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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.def("predict",
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[](vision::detection::PPYOLOE& 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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pybind11::class_<vision::detection::PPYOLO, FastDeployModel>(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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.def("predict",
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[](vision::detection::PPYOLO& 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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pybind11::class_<vision::detection::PPYOLOv2, FastDeployModel>(m, "PPYOLOv2")
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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::PPYOLOv2& 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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pybind11::class_<vision::detection::PicoDet, FastDeployModel>(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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.def("predict",
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[](vision::detection::PicoDet& 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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pybind11::class_<vision::detection::PaddleYOLOX, FastDeployModel>(
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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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.def("predict",
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[](vision::detection::PaddleYOLOX& 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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pybind11::class_<vision::detection::FasterRCNN, FastDeployModel>(m,
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"FasterRCNN")
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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::FasterRCNN& 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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pybind11::class_<vision::detection::YOLOv3, FastDeployModel>(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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.def("predict",
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[](vision::detection::YOLOv3& 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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pybind11::class_<vision::detection::MaskRCNN, FastDeployModel>(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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.def("predict",
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[](vision::detection::MaskRCNN& 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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}
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} // namespace fastdeploy
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