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[Model] Support YOLOv8 (#1137)

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* add GPL lisence

* add GPL-3.0 lisence

* add GPL-3.0 lisence

* add GPL-3.0 lisence

* support yolov8

* add pybind for yolov8

* add yolov8 readme

Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
This commit is contained in:
WJJ1995
2023-01-16 11:24:23 +08:00
committed by GitHub
parent a4b94b2c93
commit 02bd22422e
28 changed files with 1448 additions and 80 deletions
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122
fastdeploy/vision/detection/contrib/yolov8/yolov8_pybind.cc Normal file
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// 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 {
void BindYOLOv8(pybind11::module& m) {
pybind11::class_<vision::detection::YOLOv8Preprocessor>(m,
"YOLOv8Preprocessor")
.def(pybind11::init<>())
.def(
"run",
[](vision::detection::YOLOv8Preprocessor& self,
std::vector<pybind11::array>& im_list) {
std::vector<vision::FDMat> images;
for (size_t i = 0; i < im_list.size(); ++i) {
images.push_back(vision::WrapMat(PyArrayToCvMat(im_list[i])));
}
std::vector<FDTensor> outputs;
std::vector<std::map<std::string, std::array<float, 2>>> ims_info;
if (!self.Run(&images, &outputs, &ims_info)) {
throw std::runtime_error(
"Failed to preprocess the input data in YOLOv8Preprocessor.");
}
for (size_t i = 0; i < outputs.size(); ++i) {
outputs[i].StopSharing();
}
return make_pair(outputs, ims_info);
})
.def_property("size", &vision::detection::YOLOv8Preprocessor::GetSize,
&vision::detection::YOLOv8Preprocessor::SetSize)
.def_property("padding_value",
&vision::detection::YOLOv8Preprocessor::GetPaddingValue,
&vision::detection::YOLOv8Preprocessor::SetPaddingValue)
.def_property("is_scale_up",
&vision::detection::YOLOv8Preprocessor::GetScaleUp,
&vision::detection::YOLOv8Preprocessor::SetScaleUp)
.def_property("is_mini_pad",
&vision::detection::YOLOv8Preprocessor::GetMiniPad,
&vision::detection::YOLOv8Preprocessor::SetMiniPad)
.def_property("stride", &vision::detection::YOLOv8Preprocessor::GetStride,
&vision::detection::YOLOv8Preprocessor::SetStride);
pybind11::class_<vision::detection::YOLOv8Postprocessor>(
m, "YOLOv8Postprocessor")
.def(pybind11::init<>())
.def("run",
[](vision::detection::YOLOv8Postprocessor& self,
std::vector<FDTensor>& inputs,
const std::vector<std::map<std::string, std::array<float, 2>>>&
ims_info) {
std::vector<vision::DetectionResult> results;
if (!self.Run(inputs, &results, ims_info)) {
throw std::runtime_error(
"Failed to postprocess the runtime result in "
"YOLOv8Postprocessor.");
}
return results;
})
.def("run",
[](vision::detection::YOLOv8Postprocessor& self,
std::vector<pybind11::array>& input_array,
const std::vector<std::map<std::string, std::array<float, 2>>>&
ims_info) {
std::vector<vision::DetectionResult> results;
std::vector<FDTensor> inputs;
PyArrayToTensorList(input_array, &inputs, /*share_buffer=*/true);
if (!self.Run(inputs, &results, ims_info)) {
throw std::runtime_error(
"Failed to postprocess the runtime result in "
"YOLOv8Postprocessor.");
}
return results;
})
.def_property("conf_threshold",
&vision::detection::YOLOv8Postprocessor::GetConfThreshold,
&vision::detection::YOLOv8Postprocessor::SetConfThreshold)
.def_property("nms_threshold",
&vision::detection::YOLOv8Postprocessor::GetNMSThreshold,
&vision::detection::YOLOv8Postprocessor::SetNMSThreshold)
.def_property("multi_label",
&vision::detection::YOLOv8Postprocessor::GetMultiLabel,
&vision::detection::YOLOv8Postprocessor::SetMultiLabel);
pybind11::class_<vision::detection::YOLOv8, FastDeployModel>(m, "YOLOv8")
.def(pybind11::init<std::string, std::string, RuntimeOption,
ModelFormat>())
.def("predict",
[](vision::detection::YOLOv8& self, pybind11::array& data) {
auto mat = PyArrayToCvMat(data);
vision::DetectionResult res;
self.Predict(mat, &res);
return res;
})
.def("batch_predict",
[](vision::detection::YOLOv8& 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::DetectionResult> results;
self.BatchPredict(images, &results);
return results;
})
.def_property_readonly("preprocessor",
&vision::detection::YOLOv8::GetPreprocessor)
.def_property_readonly("postprocessor",
&vision::detection::YOLOv8::GetPostprocessor);
}
} // namespace fastdeploy