dev with docker and jupyter notebook!
- docker and docker-compose
- Nvidia GPU and GPU container runtime (optional)
- make (optional)
make devopen http://localhost:1145 in your browser, default password is 114514
template ipynb file is in ./video folder, you should put video in here
- (optional) use code completion in jupyter notebook
load yuuno plugin in jupyter notebook, then you can preview any frame
the playground image has sshd installed, you can ssh into the container to dev
- default port: 1022 (1022:22)
- user: root
- password: 123456
- system: Ubuntu 22.04
- GCC/G++: 13
- python: 3.10
- FFmpeg: 8.0
- Static FFmpeg: 8.0 (/static-ffmpeg/ffmpeg)
- VapourSynth: R70
- x264: latest
- x265: 4.1
- svt-av1-psy: latest
- aom: latest
- libvpx: latest
- fdk-aac: latest
- libass: latest
- CUDA toolkit: 12.9
- PyTorch: 2.8.0+cu128 ['sm_70', 'sm_75', 'sm_80', 'sm_86', 'sm_90', 'sm_100', 'sm_120']
- cupy: cuda12x
mbfunc
ccrestoration
ccvfi
vsutil
mvsfuncbestsource.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.sobuild image (default for FinalRip) and playground image
make pt && make pgThis project is licensed under the GPL-3.0 license - see the LICENSE file for details.