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My implementation of frame differencing for calculating the number of cars from a video footage

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Frame differencing Object Tracking

My implementation of frame differencing for calculating the number of cars from video footage. When looking through the code you could notice that I am using my own function for applying kernels, feel free to rewrite it using OpenCV's native function, this should speed up the run time.

There are a few things in one file:

  • icv_filter - applies a kernel
  • icv_pixel_frame_differencing - frame differencing
  • icv_generate_reference_frame - generates a reference frame from a video input
  • icv_count_objects - counts the number of objects in each video frame, using the reference frame computed from a video stream

The project is using Python 3.6.

List of Dependencies:

  • OpenCV

  • NumPy

NOT JUPYTER NOTEBOOK

Run from terminal, PyCharm, or from anything else that makes you happy:)

Everything else you need to know is in the comments.

Star, fork, do your thing.

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My implementation of frame differencing for calculating the number of cars from a video footage

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