Releases · EutropicAI/FinalRip

27 Sep 04:32

Tohrusky

v0.5.0

b641b0f

v0.5.0 Latest

Latest

What's new?

ccrestoration and ccvfi are no longer maintained, consider using cccv instead.
In cccv, we have implemented most of the features from ccrestoration and ccvfi, Enjoy!

Encode Environment

https://github.com/EutropicAI/vs-playground/releases/tag/v0.4.0

Assets 2

05 Sep 13:40

Tohrusky

v0.4.0

a5c26f0

v0.4.0

What's new?

Added support for NVIDIA 50-series GPUs and NVENC.
Updated all frontend & backend dependencies to latest versions.
Merged the frontend repo into main; the full CI/CD pipeline now runs in GitHub Actions.
Fixed several legacy issues.

Breaking Changes

ROCm support has been deprecated: considering the maintenance cost, we will no longer maintain the official ROCm encode image.
All component docker images now published under one repo (lychee0/finalrip) with tag prefixes:

Old reference	New reference (≥ v0.4.0)
`lychee0/finalrip-xxx:yyy`	`lychee0/finalrip:xxx-yyy`
`lychee0/finalrip-dashboard:latest`	`lychee0/finalrip:dashboard`
`lychee0/finalrip-worker-encode:cuda-dev`	`lychee0/finalrip:worker-encode-cuda-dev`

Encode Environment

https://github.com/EutropicAI/vs-playground/releases/tag/v0.3.2

Assets 2

31 Jan 22:53

github-actions

v0.3.0

8406cd8

v0.3.0

vs-pytorch v0.2.0
dashboard v0.3.0

Breaking Changes

Support more flexible encode param format: now you should specify the output file path FINALRIP_ENCODED_CLIP.mkv, see templates: https://github.com/TensoRaws/vs-playground/tree/main/templates

This version use `vs-pytorch` v0.2.0 as the base container for video processing, here's the release note:

Base Image: vs-ffmpeg-docker:v0.1.0

mbfunc v0.1.0
ccrestoration v0.2.1
ccvfi v0.0.1

We are excited to announce the v0.2.0 release of `vs-pytorch`, which includes significant improvements and optimizations to enhance performance and reduce docker image size:

Two-stage build: build ffmpeg and encoders at vs-ffmpeg-docker in GitHub Actions, then build vs-pytorch and vs-playground in CircleCI
Removal of Conda: we have removed Conda from the Docker image
Self-Compiled Encoders and Filters: all encoders and filters are now self-compiled, ensuring optimal compatibility and performance within the Docker environment
Self-Compiled Common VapourSynth Filters: we have compiled a set of commonly used VapourSynth filters to provide a more comprehensive and ready-to-use environment for video processing
AI Optimization: optimized AI inference speed, and support experimental video frame interpolation by ccvfi
Our VapourSynth function library: mbfunc

Environment Details:

- system: Ubuntu 22.04
- GCC/G++: 13
- python: 3.10
- FFmpeg: latest
- VapourSynth: R70
- x264: latest
- x265: 4.1
- svt-av1-psy: latest
- aom: latest
- libvpx: latest
- fdk-aac: latest
- libass: latest

VapourSynth Python Plugin List

mbfunc
ccrestoration
ccvfi
vsutil
mvsfunc
havsfunc
JET's funcs

VapourSynth C++ Plugin List

bestsource.so
libaddgrain.so
libakarin.so
libassrender.so
libbilateral.so
libbm3dcpu.so
libbm3dcuda.so
libbm3dcuda_rtc.so
libboxblur.so
libbwdif.so
libcas.so
libctmf.so
libd2vsource.so
libdctfilter.so
libdescale.so
libdfttest2_cpu.so
libdfttest2_cuda.so
libdfttest2_nvrtc.so
libeedi2.so
libeedi3m.so
libffms2.so
libfillborders.so
libfluxsmooth.so
libfmtconv.so
libhqdn3d.so
libils.so
libmiscfilters.so
libmvtools.so
libneo-dfttest.so
libneo-f3kdb.so
libneo-fft3d.so
libnnedi3.so
libremapframes.so
libremovegrain.so
libretinex.so
libsangnom.so
libtcanny.so
libtedgemask.so
libttempsmooth.so
libvsnlm_cuda.so
libvsznedi3.so

Assets 2