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| | | * `yolo-voc.cfg` (256 MB VOC-model) - require 4 GB GPU-RAM: http://pjreddie.com/media/files/yolo-voc.weights |
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| | | * `tiny-yolo.cfg` (60 MB COCO-model) - require 1 GB GPU-RAM: http://pjreddie.com/media/files/tiny-yolo.weights |
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| | | * `tiny-yolo-voc.cfg` (60 MB VOC-model) - require 1 GB GPU-RAM: http://pjreddie.com/media/files/tiny-yolo-voc.weights |
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| | | * `yolo9000.cfg` (186 MB Yolo9000-model) - require 4 GB GPU-RAM: http://pjreddie.com/media/files/yolo9000.weights |
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| | | Put it near compiled: darknet.exe |
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| | | * `CUDNN=1` to build with cuDNN v5/v6 to accelerate training by using GPU |
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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 suuport to accelerate by using multi-core CPU |
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| | | * `LIBSO=1` to build an library `darknet.so` and binary runable file `uselib` that uses this library. How to use this SO-library from your own code - you can look at C++ example: https://github.com/AlexeyAB/darknet/blob/master/src/yolo_console_dll.cpp |
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| | | * `OPENMP=1` to build with OpenMP support to accelerate Yolo by using multi-core CPU |
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| | | * `LIBSO=1` to build a library `darknet.so` and binary runable file `uselib` that uses this library. How to use this SO-library from your own code - you can look at C++ example: https://github.com/AlexeyAB/darknet/blob/master/src/yolo_console_dll.cpp |
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| | | ### How to compile on Windows: |
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| | | 1. If you have MSVS 2015, CUDA 8.0 and OpenCV 3.0 (with paths: `C:\opencv_3.0\opencv\build\include` & `C:\opencv_3.0\opencv\build\x64\vc14\lib`), then start MSVS, open `build\darknet\darknet.sln`, set **x64** and **Release**, and do the: Build -> Build darknet |
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| | | 1. If you have **MSVS 2015, CUDA 8.0 and OpenCV 3.0** (with paths: `C:\opencv_3.0\opencv\build\include` & `C:\opencv_3.0\opencv\build\x64\vc14\lib`), then start MSVS, open `build\darknet\darknet.sln`, set **x64** and **Release**, and do the: Build -> Build darknet |
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| | | 1.1. Find files `opencv_world320.dll` and `opencv_ffmpeg320_64.dll` in `C:\opencv_3.0\opencv\build\x64\vc14\bin` and put it near with `darknet.exe` |
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| | | 1.1. Find files `opencv_world320.dll` and `opencv_ffmpeg320_64.dll` in `C:\opencv_3.0\opencv\build\x64\vc14\bin` and put it near with `darknet.exe` |
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| | | 2. If you have other version of CUDA (not 8.0) then open `build\darknet\darknet.vcxproj` by using Notepad, find 2 places with "CUDA 8.0" and change it to your CUDA-version, then do step 1 |
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| | | 2. If you have other version of **CUDA (not 8.0)** then open `build\darknet\darknet.vcxproj` by using Notepad, find 2 places with "CUDA 8.0" and change it to your CUDA-version, then do step 1 |
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| | | 3. If you have OpenCV 2.4.13 instead of 3.0 then you should change pathes after `\darknet.sln` is opened |
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| | | 3. If you **don't have GPU**, but have **MSVS 2015 and OpenCV 3.0** (with paths: `C:\opencv_3.0\opencv\build\include` & `C:\opencv_3.0\opencv\build\x64\vc14\lib`), then start MSVS, open `build\darknet\darknet_no_gpu.sln`, set **x64** and **Release**, and do the: Build -> Build darknet |
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| | | 3.1 (right click on project) -> properties -> C/C++ -> General -> Additional Include Directories: `C:\opencv_2.4.13\opencv\build\include` |
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| | | 4. If you have **OpenCV 2.4.13** instead of 3.0 then you should change pathes after `\darknet.sln` is opened |
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| | | 4.1 (right click on project) -> properties -> C/C++ -> General -> Additional Include Directories: `C:\opencv_2.4.13\opencv\build\include` |
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| | | 3.2 (right click on project) -> properties -> Linker -> General -> Additional Library Directories: `C:\opencv_2.4.13\opencv\build\x64\vc14\lib` |
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| | | 4.2 (right click on project) -> properties -> Linker -> General -> Additional Library Directories: `C:\opencv_2.4.13\opencv\build\x64\vc14\lib` |
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| | | 4. If you have other version of OpenCV 2.4.x (not 3.x) then you also should change lines like `#pragma comment(lib, "opencv_core2413.lib")` in the file `\src\detector.c` |
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| | | 5. If you have other version of OpenCV 2.4.x (not 3.x) then you also should change lines like `#pragma comment(lib, "opencv_core2413.lib")` in the file `\src\detector.c` |
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| | | 5. If you want to build with CUDNN to speed up then: |
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| | | 6. 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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