Camera Motion Detection
This project uses optical flow to determine camera motion (pans and zooms).
NOTE: I’m not great at CV stuff so please excuse the probably not-ideal way of doing things here. And big thanks to Golan Levin and Alexander Porter for helping me figure it out…
Usage
detect.py will analyze a video frame by frame and record a csv file containing average camera motion angle, magnitude and “zoom factor.” Zoomy-ness is determined by what percentage of pixels appear to be moving away from the center of the image.
To run:
python detect.py somevideo.mp4
If you have CUDA you can run the GPU optimized version with:
python detect.py somevideo.mp4 --gpu
You can also preview the analysis with:
python detect.py somevideo.mp4 --preview
Rendering out different camera motions
You can make use of the generated csv file in a few different ways. I’ve also included a render.py script that attempts to extract zooming and panning shots (your mileage may vary with it!).
To save out all the zoom shots:
python render.py somevideo.mp4 --zooms --outname zooms.mp4
If you have mpv installed you can also preview this without rendering a new file:
python render.py somevideo.mp4 --zooms --preview
For panning shots, specify the desired panning angle like so:
python render.py somevideo.mp4 --pans --angle 180
Installation
CPU
Install the requirements with:
pip install -r requirements.txt
You’re done!
GPU
If you’ve got an nvidia card you can use the GPU version which is significantly faster. You need opencv with cuda which you can either compile yourself or use a docker image.
