A yolo windows version (for object detection)

Contributtors: https://github.com/pjreddie/darknet/graphs/contributors

This repository is forked from: https://github.com/frischzenger/yolo-windows Which is forked from Linux-version: https://github.com/pjreddie/darknet

• MS Visual Studio 2013 (v120)
• CUDA 6.5 for Windows x64: https://developer.nvidia.com/cuda-toolkit-65
• OpenCV 2.4.9: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.4.9/opencv-2.4.9.exe/download
  • To compile without OpenCV - remove define OPENCV from: Visual Studio->Project->Properties->C/C++->Preprocessor
  • To compile with different OpenCV version - change in file yolo_kernels.cu each string #pragma comment(lib, "opencv_core249.lib") from 249 to required version.
  • With OpenCV will show image or video detection in window and store result to test_dnn_out.avi

• yolo.cfg (1 GB) - require 4 GB GPU-RAM: http://pjreddie.com/media/files/yolo.weights
• yolo-small.cfg (359 MB) - require 2 GB GPU-RAM: http://pjreddie.com/media/files/yolo-small.weights
• yolo-tiny.cfg (172 MB) - require 1 GB GPU-RAM: http://pjreddie.com/media/files/yolo-tiny.weights

Others: https://www.youtube.com/channel/UC7ev3hNVkx4DzZ3LO19oebg

More details: http://pjreddie.com/darknet/yolo/

• darknet.cmd - initialization with 1 GB model yolo.weights & yolo.cfg and get command prompt: enter the jpg-image-filename
• darknet_demo.cmd - initialization with 1 GB model yolo.weights & yolo.cfg and play your video file which you must rename to: test.mp4
• darknet_demo_small.cmd - initialization with 359 MB small model yolo-small.weights & yolo-small.cfg and play your video file which you must rename to: test.mp4
• darknet_net_cam.cmd - initialization with 1 GB model, play video from network video-camera mjpeg-stream and store result to: test_dnn_out.avi

1. Download for Android phone mjpeg-stream soft: IP Webcam / Smart WebCam

Smart WebCam - preferably: https://play.google.com/store/apps/details?id=com.acontech.android.SmartWebCam IP Webcam: https://play.google.com/store/apps/details?id=com.pas.webcam

2. Connect your Android phone to computer by WiFi (through a WiFi-router) or USB
3. Start Smart WebCam on your phone
4. Replace the address below, on shown in the phone application (Smart WebCam) and launch:

darknet.exe yolo demo yolo.cfg yolo.weights http://192.168.0.80:8080/video?dummy=param.mjpg -i 0

Windows (Visual Studio) Support Now yolo supports windows with Visual Studio. Just change the include directories / library directories to your own ones, and compile the codes with X64 Release mode. You may need pthread-windows while compiling and linking