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| | | * both Windows and Linux |
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| | | * both OpenCV 3.x and OpenCV 2.4.13 |
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| | | * both cuDNN 5 and cuDNN 6 |
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| | | * both cuDNN v5-v7 |
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| | | * CUDA >= 7.5 |
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| | | * also create SO-library on Linux and DLL-library on Windows |
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| | | |
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| | | ##### Requires: |
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| | | * **Linux GCC>=4.9 or Windows MS Visual Studio 2015 (v140)**: https://go.microsoft.com/fwlink/?LinkId=532606&clcid=0x409 (or offline [ISO image](https://go.microsoft.com/fwlink/?LinkId=615448&clcid=0x409)) |
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| | | * **CUDA 8.0**: https://developer.nvidia.com/cuda-downloads |
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| | | * **CUDA 9.1**: https://developer.nvidia.com/cuda-downloads |
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| | | * **OpenCV 3.x**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.2.0/opencv-3.2.0-vc14.exe/download |
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| | | * **or OpenCV 2.4.13**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.4.13/opencv-2.4.13.2-vc14.exe/download |
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| | | - OpenCV allows to show image or video detection in the window and store result to file that specified in command line `-out_filename res.avi` |
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| | | Just do `make` in the darknet directory. |
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| | | Before make, you can set such options in the `Makefile`: [link](https://github.com/AlexeyAB/darknet/blob/9c1b9a2cf6363546c152251be578a21f3c3caec6/Makefile#L1) |
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| | | * `GPU=1` to build with CUDA to accelerate by using GPU (CUDA should be in `/usr/local/cuda`) |
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| | | * `CUDNN=1` to build with cuDNN v5/v6 to accelerate training by using GPU (cuDNN should be in `/usr/local/cudnn`) |
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| | | * `CUDNN=1` to build with cuDNN v5-v7 to accelerate training by using GPU (cuDNN should be in `/usr/local/cudnn`) |
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| | | * `OPENCV=1` to build with OpenCV 3.x/2.4.x - allows to detect on video files and video streams from network cameras or web-cams |
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| | | * `DEBUG=1` to bould debug version of Yolo |
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| | | * `OPENMP=1` to build with OpenMP support to accelerate Yolo by using multi-core CPU |
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| | | 5. If you want to build with CUDNN to speed up then: |
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| | | * download and install **cuDNN 6.0 for CUDA 8.0**: https://developer.nvidia.com/cudnn |
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| | | * download and install **cuDNN 7.0 for CUDA 9.1**: https://developer.nvidia.com/cudnn |
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| | | |
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| | | * add Windows system variable `cudnn` with path to CUDNN: https://hsto.org/files/a49/3dc/fc4/a493dcfc4bd34a1295fd15e0e2e01f26.jpg |
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