sniklaus/pytorch-liteflownet
a reimplementation of LiteFlowNet in PyTorch that matches the official Caffe version
This project helps researchers and engineers analyze the motion between two images. It takes in a pair of images and outputs an 'optical flow' map, which visually represents how pixels move from the first image to the second. This is useful for anyone working with video analysis, motion tracking, or computer vision tasks where understanding movement is key.
431 stars. No commits in the last 6 months.
Use this if you need to precisely quantify and visualize pixel movement between two consecutive images, especially in a research or prototyping context.
Not ideal if you need a guaranteed correct, production-ready optical flow solution, as this is a personal reimplementation and may have numerical deviations.
Stars
431
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81
Language
Python
License
GPL-3.0
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Last pushed
Jan 06, 2025
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