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| | | * **OpenCV 2.4.9**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.4.9/opencv-2.4.9.exe/download |
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| | | - To compile without OpenCV - remove define OPENCV from: Visual Studio->Project->Properties->C/C++->Preprocessor |
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| | | - To compile with different OpenCV version - change in file yolo.c each string look like **#pragma comment(lib, "opencv_core249.lib")** from 249 to required version. |
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| | | - With OpenCV will show image or video detection in window |
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| | | - With OpenCV will show image or video detection in window and store result to: test_dnn_out.avi |
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| | | |
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| | | ##### Pre-trained models for different cfg-files can be downloaded from (smaller -> faster & lower quality): |
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| | | * `yolo.cfg` (256 MB) - require 4 GB GPU-RAM: http://pjreddie.com/media/files/yolo-voc.weights |
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| | | * `yolo-tiny.cfg` (60 MB) - require 1 GB GPU-RAM: http://pjreddie.com/media/files/tiny-yolo-voc.weights |
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| | | * `yolo.cfg` (256 MB COCO-model) - require 4 GB GPU-RAM: http://pjreddie.com/media/files/yolo.weights |
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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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| | | Put it near compiled: darknet.exe |
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| | | You can get cfg-files by path: `darknet/cfg/` |
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| | | |
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| | | ##### Examples of results: |
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| | | [](https://www.youtube.com/watch?v=VOC3huqHrss "Everything Is AWESOME") |
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| | | Others: https://www.youtube.com/channel/UC7ev3hNVkx4DzZ3LO19oebg |
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| | | |
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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, and store result to: test_dnn_out.avi |
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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) and store result to: test_dnn_out.avi |
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| | | * `darknet_web_cam_voc.cmd` - initialization with 256 MB VOC-model, play video from Web-Camera number #0 and store result to: test_dnn_out.avi |
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| | | |
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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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| | | * Alternative method 256 MB COCO-model - image: `darknet.exe detect 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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| | | * 256 MB VOC-model - WebCamera #0: `darknet.exe detector demo data/voc.data yolo-voc.cfg yolo-voc.weights -c 0` |
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| | | |
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| | | ##### For using network video-camera mjpeg-stream with any Android smartphone: |
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| | | 3. Start Smart WebCam on your phone |
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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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| | | ``` |
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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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| | | ``` |
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| | | |
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| | | * 256 MB COCO-model: `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: `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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| | | |
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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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| | | `C:\opencv_2.4.9\opencv\build\include;..\..\3rdparty\include;%(AdditionalIncludeDirectories);$(CudaToolkitIncludeDir);$(cudnn)\include` |
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| | | - right click on project -> Build dependecies -> Build Customizations -> set check on CUDA 8.0 or what version you have - for example as here: http://devblogs.nvidia.com/parallelforall/wp-content/uploads/2015/01/VS2013-R-5.jpg |
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| | | - add to project all .c & .cu files from yolo-windows\src |
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| | | - add to project all .c & .cu files from `\src` |
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| | | - (right click on project) -> properties -> Linker -> General -> Additional Library Directories, put here: |
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| | | `C:\opencv_2.4.9\opencv\build\x64\vc12\lib;$(CUDA_PATH)lib\$(PlatformName);$(cudnn)\lib\x64;%(AdditionalLibraryDirectories)` |
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| | | `OPENCV;_TIMESPEC_DEFINED;_CRT_SECURE_NO_WARNINGS;GPU;WIN32;NDEBUG;_CONSOLE;_LIB;%(PreprocessorDefinitions)` |
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| | | - compile to .exe (X64 & Release) and put .dll`s near with .exe: |
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| | | `pthreadVC2.dll, pthreadGC2.dll` from yolo-windows\3rdparty\dll\x64 |
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| | | `pthreadVC2.dll, pthreadGC2.dll` from \3rdparty\dll\x64 |
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| | | `cusolver64_80.dll, curand64_80.dll, cudart64_80.dll, cublas64_80.dll` - 80 for CUDA 8.0 or your version, from C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin |
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