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Video Object Recognition

Using YOLO9000, classify objects in a video (made to support a wider range of computers than YOLO-9000 supports)

Dependencies

Usage

  1. Run ffmpeg -i video.mp4 "frames/out-%08d.jpg" on your desired video
  2. Put the frames folder into YOLO-9000's folder
  3. Put strain.py into darknet/ and run the script
  4. Concatenate the frames back into a video with ffmpeg -framerate 25 -i out_%08d.jpg output.mp4 (framerate will need adjusting)

Known issues

  • The script takes a long time to run. This is because the nueral network is running on the CPU for compatability reasons. Machine learning is much faster on a GPU but very few GPUs fully support NN/ML. To remedy, run overnight.

Example

I collected clips of Sydney and fed it through the classifier and paired it with music to produce this result.

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Using YOLO9000, classify objects in a video

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