vapoursynth version for DistilDRBA based on vs-rife.
This project is modified from HolyWu/vs-rife and achieves nearly the same interpolation quality as the original DistilDRBA project.
With TensorRT integration, it achieves a 400% acceleration, enabling real-time playback on high-performance NVIDIA GPUs.
- PyTorch 2.6.0 or later
- VapourSynth R66 or later
trt requires additional packages: (If encountering issues, you may skip installing this dependency and specify trt=False when using drba.)
- TensorRT 10.7.0.post1 or later
- Torch-TensorRT 2.6.0 or later
To install the latest stable version of PyTorch, Torch-TensorRT and cupy, run:
pip install -U packaging setuptools wheel
pip install -U torch torchvision torch-tensorrt --index-url https://download.pytorch.org/whl/cu128 --extra-index-url https://pypi.nvidia.com
pip install -U vsdrba_distilled==1.0.0
Note: Please make sure to install all dependencies listed in the Dependencies section before performing the steps in the Installation section.
If you want to download all models at once, run python -m vsdrba_distilled. If you prefer to only download the model you
specified at first run, set auto_download=True in drba_distilled().
from vsdrba_distilled import drba_distilled
ret = drba_distilled(clip, trt=True, factor_num=2, factor_den=1, scale=1.0, model="v1", auto_download=True)See __init__.py for the description of the parameters.
| model | scale | os | hardware | arch | speed(fps) 720 | speed(fps) 1080 | vram 720 | vram 1080 | backend | verified output | batch | level | streams | threads | trtexec shape | precision | usage |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| drba_distilled v1 | 2x | Linux | rtx5070 / 14600kf | drba_distilled | 251 | 115 | 1.8gb | 2.9gb | torch+trt cu128 | yes, works | 1 | 5 | - | 1 | static | RGBH | drba_distilled(clip, trt=True, model="v1", trt_optimization_level=5) |
| drba_distilled v2_lite | 2x | Linux | rtx5070 / 14600kf | drba_distilled | 999+ | 700 | - | - | torch+trt cu128 | yes, works | 1 | 5 | - | 1 | static | RGBH | drba_distilled(clip, trt=True, model="v1", trt_optimization_level=5) |
This project is supported by SVFI Development Team.