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Now that we have created the flow for two corresponding images in the last issue, let's start working on creating images in consecutive images.
Let's say we created the flow from images 0000.png and 0001.png.
We now need to create the flow from 0001.png and 0002.png.
Doing so, we need to create the flow between subsequent flows from x.png and x+1.png (where x is of the form XXXX where X is between [0,9]).
To do this, first:
Tasks for the next week
The purpose is to understand how neural networks work.
Deadline: Monday (May 23rd, 2022)
The following are the goals for next week:
Now that preliminaries are out of the way, the next step is to extract the flow from a video.
Estimated time of completion: 2 weeks (5 days extra)
You can find the implementation here: https://github.com/NVlabs/PWC-Net
For the Pytorch implementation, please look at: https://github.com/sniklaus/pytorch-pwc
Also install flowiz from here : https://github.com/georgegach/flowiz (pip install flowiz -U)
After a week:
You should be able to implement and generate the flow.
Now, download the GOPRO dataset from here: https://seungjunnah.github.io/Datasets/gopro (either GoPro or GoPro_Large)
Explore what to do with it.
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