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* first commit for yolov7 * pybind for yolov7 * CPP README.md * CPP README.md * modified yolov7.cc * README.md * python file modify * delete license in fastdeploy/ * repush the conflict part * README.md modified * README.md modified * file path modified * file path modified * file path modified * file path modified * file path modified * README modified * README modified * move some helpers to private * add examples for yolov7 * api.md modified * api.md modified * api.md modified * YOLOv7 * yolov7 release link * yolov7 release link * yolov7 release link * copyright * change some helpers to private * change variables to const and fix documents.
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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. | ||
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#include "fastdeploy/vision.h" | ||
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int main() { | ||
namespace vis = fastdeploy::vision; | ||
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std::string model_file = "../resources/models/yolov7.onnx"; | ||
std::string img_path = "../resources/images/horses.jpg"; | ||
std::string vis_path = "../resources/outputs/wongkinyiu_yolov7_vis_result.jpg"; | ||
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auto model = vis::wongkinyiu::YOLOv7(model_file); | ||
if (!model.Initialized()) { | ||
std::cerr << "Init Failed! Model: " << model_file << std::endl; | ||
return -1; | ||
} else { | ||
std::cout << "Init Done! Model:" << model_file << std::endl; | ||
} | ||
model.EnableDebug(); | ||
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cv::Mat im = cv::imread(img_path); | ||
cv::Mat vis_im = im.clone(); | ||
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vis::DetectionResult res; | ||
if (!model.Predict(&im, &res)) { | ||
std::cerr << "Prediction Failed." << std::endl; | ||
return -1; | ||
} else { | ||
std::cout << "Prediction Done!" << std::endl; | ||
} | ||
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// 输出预测框结果 | ||
std::cout << res.Str() << std::endl; | ||
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// 可视化预测结果 | ||
vis::Visualize::VisDetection(&vis_im, res); | ||
cv::imwrite(vis_path, vis_im); | ||
std::cout << "Detect Done! Saved: " << vis_path << std::endl; | ||
return 0; | ||
} |
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from . import meituan | ||
from . import megvii | ||
from . import visualize | ||
from . import wongkinyiu |
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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. | ||
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from __future__ import absolute_import | ||
import logging | ||
from ... import FastDeployModel, Frontend | ||
from ... import fastdeploy_main as C | ||
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class YOLOv7(FastDeployModel): | ||
def __init__(self, | ||
model_file, | ||
params_file="", | ||
runtime_option=None, | ||
model_format=Frontend.ONNX): | ||
# 调用基函数进行backend_option的初始化 | ||
# 初始化后的option保存在self._runtime_option | ||
super(YOLOv7, self).__init__(runtime_option) | ||
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self._model = C.vision.wongkinyiu.YOLOv7( | ||
model_file, params_file, self._runtime_option, model_format) | ||
# 通过self.initialized判断整个模型的初始化是否成功 | ||
assert self.initialized, "YOLOv7 initialize failed." | ||
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def predict(self, input_image, conf_threshold=0.25, nms_iou_threshold=0.5): | ||
return self._model.predict(input_image, conf_threshold, | ||
nms_iou_threshold) | ||
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# 一些跟YOLOv7模型有关的属性封装 | ||
# 多数是预处理相关,可通过修改如model.size = [1280, 1280]改变预处理时resize的大小(前提是模型支持) | ||
@property | ||
def size(self): | ||
return self._model.size | ||
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@property | ||
def padding_value(self): | ||
return self._model.padding_value | ||
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@property | ||
def is_no_pad(self): | ||
return self._model.is_no_pad | ||
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@property | ||
def is_mini_pad(self): | ||
return self._model.is_mini_pad | ||
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@property | ||
def is_scale_up(self): | ||
return self._model.is_scale_up | ||
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@property | ||
def stride(self): | ||
return self._model.stride | ||
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@property | ||
def max_wh(self): | ||
return self._model.max_wh | ||
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@size.setter | ||
def size(self, wh): | ||
assert isinstance(wh, [list, tuple]),\ | ||
"The value to set `size` must be type of tuple or list." | ||
assert len(wh) == 2,\ | ||
"The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format( | ||
len(wh)) | ||
self._model.size = wh | ||
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@padding_value.setter | ||
def padding_value(self, value): | ||
assert isinstance( | ||
value, | ||
list), "The value to set `padding_value` must be type of list." | ||
self._model.padding_value = value | ||
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@is_no_pad.setter | ||
def is_no_pad(self, value): | ||
assert isinstance( | ||
value, bool), "The value to set `is_no_pad` must be type of bool." | ||
self._model.is_no_pad = value | ||
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@is_mini_pad.setter | ||
def is_mini_pad(self, value): | ||
assert isinstance( | ||
value, | ||
bool), "The value to set `is_mini_pad` must be type of bool." | ||
self._model.is_mini_pad = value | ||
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@is_scale_up.setter | ||
def is_scale_up(self, value): | ||
assert isinstance( | ||
value, | ||
bool), "The value to set `is_scale_up` must be type of bool." | ||
self._model.is_scale_up = value | ||
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@stride.setter | ||
def stride(self, value): | ||
assert isinstance( | ||
value, int), "The value to set `stride` must be type of int." | ||
self._model.stride = value | ||
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@max_wh.setter | ||
def max_wh(self, value): | ||
assert isinstance( | ||
value, float), "The value to set `max_wh` must be type of float." | ||
self._model.max_wh = value |
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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. | ||
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#include "fastdeploy/pybind/main.h" | ||
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namespace fastdeploy { | ||
void BindWongkinyiu(pybind11::module& m) { | ||
auto wongkinyiu_module = | ||
m.def_submodule("wongkinyiu", "https://github.com/WongKinYiu/yolov7"); | ||
pybind11::class_<vision::wongkinyiu::YOLOv7, FastDeployModel>( | ||
wongkinyiu_module, "YOLOv7") | ||
.def(pybind11::init<std::string, std::string, RuntimeOption, Frontend>()) | ||
.def("predict", | ||
[](vision::wongkinyiu::YOLOv7& self, pybind11::array& data, | ||
float conf_threshold, float nms_iou_threshold) { | ||
auto mat = PyArrayToCvMat(data); | ||
vision::DetectionResult res; | ||
self.Predict(&mat, &res, conf_threshold, nms_iou_threshold); | ||
return res; | ||
}) | ||
.def_readwrite("size", &vision::wongkinyiu::YOLOv7::size) | ||
.def_readwrite("padding_value", | ||
&vision::wongkinyiu::YOLOv7::padding_value) | ||
.def_readwrite("is_mini_pad", &vision::wongkinyiu::YOLOv7::is_mini_pad) | ||
.def_readwrite("is_no_pad", &vision::wongkinyiu::YOLOv7::is_no_pad) | ||
.def_readwrite("is_scale_up", &vision::wongkinyiu::YOLOv7::is_scale_up) | ||
.def_readwrite("stride", &vision::wongkinyiu::YOLOv7::stride) | ||
.def_readwrite("max_wh", &vision::wongkinyiu::YOLOv7::max_wh); | ||
} | ||
} // namespace fastdeploy |
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