Mirrors/ECCV2022-RIFE
1
0
Fork 0
mirror of https://github.com/hzwer/ECCV2022-RIFE.git synced 2026-02-24 04:19:41 +01:00
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'main' of https://github.com/hzwer/arXiv2020-RIFE into main

Browse Source
This commit is contained in:
hzwer
2020-11-23 18:46:26 +08:00
parent 8ca09f6e8f b3d328ea14
commit 7edece6484
1 changed files with 9 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
README.md
View File

@@ -1,13 +1,17 @@
# RIFE Video Frame Interpolation
## [arXiv](https://arxiv.org/abs/2011.06294) | [Project Page](https://rife-vfi.github.io) | [Reddit](https://www.reddit.com/r/linux/comments/jy4jjl/opensourced_realtime_video_frame_interpolation/) | [YouTube_v1.2](https://youtu.be/LE2Dzl0oMHI)
## [arXiv](https://arxiv.org/abs/2011.06294) | [Project Page](https://rife-vfi.github.io) | [Reddit](https://www.reddit.com/r/linux/comments/jy4jjl/opensourced_realtime_video_frame_interpolation/) | [YouTube_v1.2](https://www.youtube.com/watch?v=60DX2T3zyVo&feature=youtu.be)
**11.22 News: We notice a new windows app is trying to integrate RIFE, we hope everyone to try and help them improve. You can download [Flowframes](https://nmkd.itch.io/flowframes) for free.**
**We find [a tutorial of RIFE](https://www.youtube.com/watch?v=gf_on-dbwyU&feature=emb_title) on Youtube.**
**11.20 News: I optimize the parallel processing, get 60% speedup!**
Date of recent model update: 2020.11.19, v1.2
**You can easily use [colaboratory](https://colab.research.google.com/github/hzwer/arXiv2020-RIFE/blob/main/Colab_demo.ipynb) to have a try and generate the above youtube demo.**
**Our model is currently not very suitable for 2d animation.**
**You can easily use [colaboratory](https://colab.research.google.com/github/hzwer/arXiv2020-RIFE/blob/main/Colab_demo.ipynb) to have a try and generate the [our youtube demo](https://www.youtube.com/watch?v=LE2Dzl0oMHI).**
Our model can run 30+FPS for 2X 720p interpolation on a 2080Ti GPU. Currently our method supports 2X,4X,8X interpolation for 1080p video, and multi-frame interpolation between a pair of images. Everyone is welcome to use our alpha version and make suggestions!
@@ -32,7 +36,7 @@ $ pip3 install opencv-python
* Download the pretrained models from [here](https://drive.google.com/file/d/1zYc3PEN4t6GOUoVYJjvcXoMmM3kFDNGS/view?usp=sharing).
We are optimizing the visual effects and will support animation in the future.
(我们也提供了百度网盘链接:https://pan.baidu.com/s/1YVUsusJFhZ2rWg1Zs5sOkQ 密码:88bu，把压缩包解开后放在 train_log/\*.pkl)
(我们也提供了百度网盘链接:https://pan.baidu.com/s/17mK2oTZUCMtMgmAdoifLGA 密码:h0cl，把压缩包解开后放在 train_log/\*.pkl)
* Unzip and move the pretrained parameters to train_log/\*.pkl
The models under different setting is coming soon.
@@ -43,11 +47,11 @@ You can use our [demo video](https://drive.google.com/file/d/1i3xlKb7ax7Y70khcTc
```
$ python3 inference_video.py --exp=1 --video=video.mp4
```
(generate video_2X_xxfps.mp4, you can use this script repeatly to get 4X, 8X...)
(generate video_2X_xxfps.mp4)
```
$ python3 inference_video.py --exp=2 --video=video.mp4
```
(we specificly support exp=2 for 4X interpolation)
(for 4X interpolation)
```
$ python3 inference_video.py --exp=2 --video=video.mp4 --fps=60
```