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* update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox
32 lines
1.0 KiB
Markdown
32 lines
1.0 KiB
Markdown
# 编译YOLOX示例
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当前支持模型版本为：[YOLOX v0.1.1](https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0)
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```
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# 下载和解压预测库
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wget https://bj.bcebos.com/paddle2onnx/fastdeploy/fastdeploy-linux-x64-0.0.3.tgz
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tar xvf fastdeploy-linux-x64-0.0.3.tgz
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# 编译示例代码
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mkdir build & cd build
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cmake ..
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make -j
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# 下载模型和图片
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wget https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_s.onnx
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wget https://raw.githubusercontent.com/ultralytics/yolov5/master/data/images/bus.jpg
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# 执行
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./yolox_demo
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```
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执行完后可视化的结果保存在本地`vis_result.jpg`，同时会将检测框输出在终端，如下所示
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```
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DetectionResult: [xmin, ymin, xmax, ymax, score, label_id]
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17.151855,225.294434, 805.329712, 735.578613, 0.940478, 5
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671.162109,387.403961, 809.000000, 879.525513, 0.909566, 0
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54.373432,400.188110, 204.652756, 893.662537, 0.894507, 0
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221.339310,406.614960, 347.045593, 857.299927, 0.887144, 0
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0.083759,554.987305, 61.894527, 881.098816, 0.450202, 0
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```
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