sminterpolate
Super-SloMo
sminterpolate | Super-SloMo | |
---|---|---|
6 | 1 | |
1,373 | 2,965 | |
- | - | |
0.0 | 0.0 | |
almost 4 years ago | about 1 year ago | |
Python | Python | |
MIT License | MIT License |
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sminterpolate
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How to upscale and remove watermark
For increasing fps, I recommend butterflow, but it's rather old. One of the forks has it working on a more recent version of fedora, not sure if that translates to windows easily.
- AMD Fluid Motion, how to get it to work?
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Dancing Thunder Clouds. Vqgan/Clip
For motion interpolation I used a program called butterflow: https://github.com/dthpham/butterflow. It can be hit or miss, but it's a cool tool to have your belt. In this case it added a bit of rhythmic jerkiness that made me think of adding music :-)
- One concussion please
- Open-firmware GoPro alternative?
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Frame rate booster from 24fps to 60fps for free
Butterflow is good: https://github.com/dthpham/butterflow
Super-SloMo
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Cop records huge crash with his bodycam.
No, this is clearly based on deep training based methods. Traditional algorithms wouldn't have fucked up the text that badly. The artefacts in the video practically scream "i ran this clip thru SuperSloMo".
What are some alternatives?
butterflow-ui - A graphical user interface for butterflow.
AnimeInterp - The code for CVPR21 paper "Deep Animation Video Interpolation in the Wild"
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
frame-interpolation - FILM: Frame Interpolation for Large Motion, In ECCV 2022.
hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
torchio - Medical imaging toolkit for deep learning
tabnet - PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
XVFI - [ICCV 2021, Oral 3%] Official repository of XVFI
open-lpr - Open Source and Free License Plate Recognition Software
vectory - Vectory provides a collection of tools to track and compare embedding versions.
dnn.cool - A framework for multi-task learning, where you may precondition tasks and compose them into bigger tasks. Conditional objectives and per-task evaluations and interpretations.