Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/shieman/VideoProcess
Denoise, Colorize, Upscale Resolution, Video Stabilization, Increase FPS.
https://github.com/shieman/VideoProcess
Last synced: 6 days ago
JSON representation
Denoise, Colorize, Upscale Resolution, Video Stabilization, Increase FPS.
- Host: GitHub
- URL: https://github.com/shieman/VideoProcess
- Owner: shieman
- Created: 2020-04-15T15:21:24.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-04-29T15:23:20.000Z (over 4 years ago)
- Last Synced: 2024-08-01T21:44:09.459Z (3 months ago)
- Language: C++
- Homepage:
- Size: 1.03 MB
- Stars: 27
- Watchers: 1
- Forks: 7
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# VideoProcess
I needed video and image processings for a theater project. so i implemented this tools.
Tools to denoise, colorize, upscale resolution, video stabilization, increase FPS to videos.
All that thanks to Machine Learning.
### Tools :
```
White Balance
Denoise
Video Stabilization
DAIN (extern tool)
Super Resolution
Colorization
```
# White Balance
Color White Balance.
from opencv xphoto contrib module.
# Denoise
Performs image denoising using the Block-Matching and 3D-filtering algorithm.
It works on Black and White images...
from opencv xphoto contrib module.
# Video Stabilization
Perform video stabilization.
From opencv videostab contrib module.
# DAIN
"Dain-App is a free app that let you take any form of media like movies, stop-motion, anime, cartoons,
sprites, etc and interpolate new frames, generating a bigger frame-rate from the original file."
The link : https://grisk.itch.io/dain-app
See tutos to use it. I won't explain.
Cuda app, so Nvidia graphic card only.
# Super Resolution
This module contains several learning-based algorithms for upscaling an image.
### The models :
1. EDSR
- x2, x3, x4 trained models available
- Advantage: Highly accurate
- Disadvantage: Slow and large filesize
2. ESPCN
- x2, x3, x4 trained models available
- Advantage: It is tiny and fast, and still performs well.
- Disadvantage: Perform worse visually than newer, more robust models.
3. FSRCNN
- Advantage: Fast, small and accurate
- Disadvantage: Not state-of-the-art accuracy
4. LapSRN
- x2, x4, x8 trained models available
- Advantage: The model can do multi-scale super-resolution with one forward pass.
- Disadvantage: It is slower than ESPCN and FSRCNN, and the accuracy is worse than EDSR.
from opencv dnn superres contrib module.
I hacked a part of source to include in mine to use possibility of cuda dnn.
# Colorization
Colorize Black and white (even colored) images and videos.
It uses machine learning model to predict colors.
# How it works
Windows Only. Tested on Win 10.
All the modules, except DAIN app, uses opencv 4.2 cuda 10.2.
So it's better to have a Nvidia graphic card to perform max.
Some of the tools are quite slow, even on GPU. Using them on CPU should take a lot of time.
- download repository
- install Cuda 10.2 and Cudnn 7.6.5.
- For the Windows users, i share the dll's from opencv :
Opencv downloads : http://docs.encima.fr/index.php/s/zJnnmqgzd949cJD
the file opencv_videoio_ffmpeg420_64.old is a renamed opencv_videoio_ffmpeg420_64.dll file because i did not
manage the use of ffmpeg for videos. I did not find a good way to use it, do not know why so renamed in .old,
opencv does not use it...
These files should be near .exe files or on a place that is on windows path in env vars.
- Some tools use models, place them in Models folder : http://docs.encima.fr/index.php/s/QN9QHbw8ef5bXEN
All tools work in the same way, you can find help with --help for each one.
Some parameters have default values, check thanks to --help.
Each tool can process many files in same execution. They pick files in --input dir and export results in --output dir.
They can process :
- .jpg, .png, .tif images
- .mov, .mp4 and .avi video files.
Videos are exported in .mov with avc1 codec.
### example :
SuperRes.exe --i=Input --o=Output --algo=espcn --scale=3
Multiply x3 the resolution of images and videos in Input folder, using Espcn algo, and export results in Output folder.
# Thanks
```
Opencv team - https://opencv.org/
Opencv contrib module xphoto, superres_dnn, videostab teams - https://docs.opencv.org/4.2.0/modules.html
Grisk Dain app - https://grisk.itch.io/dain-app
Dain github team - https://github.com/baowenbo/DAIN
```