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| | | Others: https://www.youtube.com/channel/UC7ev3hNVkx4DzZ3LO19oebg |
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| | | ##### Example of usage in cmd-files: |
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| | | ### How to use: |
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| | | * `darknet_demo_voc.cmd` - initialization with 256 MB model yolo-voc.weights & yolo-voc.cfg and play your video file which you must rename to: test.mp4 |
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| | | * `darknet_net_cam_voc.cmd` - initialization with 256 MB model, play video from network video-camera mjpeg-stream (also from you phone) |
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| | | ##### Example of usage in cmd-files from `build\darknet\x64\`: |
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| | | * `darknet_voc.cmd` - initialization with 256 MB VOC-model yolo-voc.weights & yolo-voc.cfg and waiting for entering the name of the image file |
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| | | * `darknet_demo_voc.cmd` - initialization with 256 MB VOC-model yolo-voc.weights & yolo-voc.cfg and play your video file which you must rename to: test.mp4 |
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| | | * `darknet_net_cam_voc.cmd` - initialization with 256 MB VOC-model, play video from network video-camera mjpeg-stream (also from you phone) |
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| | | ##### How to use on the command line: |
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| | | * 256 MB COCO-model - image: `darknet.exe detector test data/coco.data yolo.cfg yolo.weights -i 0 -thresh 0.2` |
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| | | * 256 MB VOC-model - image: `darknet.exe detector test data/voc.data yolo-voc.cfg yolo-voc.weights -i 0` |
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| | | * 256 MB COCO-model - video: `darknet.exe detector demo data/coco.data yolo.cfg yolo.weights test.mp4 -i 0` |
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| | | * 256 MB VOC-model - video: `darknet.exe detector demo data/voc.data yolo-voc.cfg yolo-voc.weights test.mp4 -i 0` |
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| | | * Alternative method 256 MB VOC-model - video: `darknet.exe yolo demo yolo-voc.cfg yolo-voc.weights test.mp4 -i 0` |
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| | | * 60 MB VOC-model for video: `darknet.exe detector demo data/voc.data tiny-yolo-voc.cfg tiny-yolo-voc.weights test.mp4 -i 0` |
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| | | * 256 MB COCO-model for net-videocam - Smart WebCam: `darknet.exe detector demo data/coco.data yolo.cfg yolo.weights http://192.168.0.80:8080/video?dummy=param.mjpg -i 0` |
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| | | * 256 MB VOC-model for net-videocam - Smart WebCam: `darknet.exe detector demo data/voc.data yolo-voc.cfg yolo-voc.weights http://192.168.0.80:8080/video?dummy=param.mjpg -i 0` |
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| | | ##### For using network video-camera mjpeg-stream with any Android smartphone: |
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| | | 4. Replace the address below, on shown in the phone application (Smart WebCam) and launch: |
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| | | ``` |
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| | | darknet.exe yolo demo yolo.cfg yolo.weights http://192.168.0.80:8080/video?dummy=param.mjpg -i 0 |
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| | | darknet.exe yolo demo yolo-voc.cfg yolo-voc.weights http://192.168.0.80:8080/video?dummy=param.mjpg -i 0 |
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| | | ``` |
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| | | ##### How to use COCO instead of VOC: |
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| | | * Get synset names from `build\darknet\x64\data\coco.names`: https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/data/coco.names |
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| | | * And change list `char *voc_names[] = ` to COCO-names in file `yolo.c`: https://github.com/AlexeyAB/darknet/blob/master/src/yolo.c#L30 |
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| | | ### How to compile: |
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| | | 1. If you have CUDA 8.0, OpenCV 2.4.9 (C:\opencv_2.4.9) and MSVS 2015 then start MSVS, open `yolo-windows\build\darknet\darknet.sln` and do the: Build -> Build darknet |
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| | | 1. If you have CUDA 8.0, OpenCV 2.4.9 (C:\opencv_2.4.9) and MSVS 2015 then start MSVS, open `build\darknet\darknet.sln` and do the: Build -> Build darknet |
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| | | 2. If you have other version of CUDA (not 8.0) then open `darknet\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 other version of OpenCV 2.4.x (not 2.4.9) then you should change pathes after `\darknet.sln` is opened |
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