#Type in overwatch code install

Pss! Line 20 and 21 make the same thing, so you can use which line you like the most). I commented line 20, because found, that resolution 960*540 works the best for pictures with initial resolution around 1280*720. You can use now resizer.py to make pictures more smaller than now. This get us 10 frames for each seconds from a video output.avi, and save those frames(images) in folder images. Use ffmpeg to get frames from the created video (create folder /images first!): ffmpeg -i output.avi -vf fps=10 images/thumb%04d.jpg -hide_banner

#Type in overwatch code install

If you will be inspired by results, welcome to training your own model on your own data.ДЇor extracting frames from output.avi you will need ffmpeg: so letвЂ™s install it! pip3 install -user ffmpeg Important: For the first time you can use trained model from my repo and donвЂ™t make images, training model etc (so skip this and go to the next part). ThatвЂ™s your gameplay, on which model will be trained.

Script was finished and you can see output.avi file here. When you will done, click on window frame and press Q. Just type in console: python3 simplestream.pyДЄnd return to game. Spend few minutes on it you will do it only once. For example, I hardcoded them and fit Overwatch window in center of a screen you might to prefer place window at the top left corner etc. Feel free to replace this line of code with values, with which you will are most comfortable. You need to fit your window gameвЂ™s with values in monitor dictionary.

Look at line 17: here you select part of the screen to capture.