DPIR function for VapourSynth
Project description
DPIR
Plug-and-Play Image Restoration with Deep Denoiser Prior, based on https://github.com/cszn/DPIR.
Dependencies
- NumPy
- ONNX Runtime. CUDA and TensorRT require
onnxruntime-gpu, while DirectML requiresonnxruntime-directml. Note that only one ofonnxruntime,onnxruntime-gpuandonnxruntime-directmlshould be installed at a time in any one environment. - VapourSynth R55 or newer.
- (Optional) CUDA Toolkit
- (Optional) cuDNN
- (Optional) TensorRT
Installation
pip install --upgrade vsdpir
python -m vsdpir
Usage
from vsdpir import DPIR
ret = DPIR(clip)
See __init__.py for the description of the parameters.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
File details
Details for the file vsdpir-2.2.0-py3-none-any.whl.
File metadata
- Download URL: vsdpir-2.2.0-py3-none-any.whl
- Upload date:
- Size: 7.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | e10c4cab6f0d8c64f87627423f99922c5bbeabb9d5330110c53333d758b9067e |
|
| MD5 | 43dcef9754dbe28847deb5505cc633ba |
|
| BLAKE2b-256 | b53766736377c8a697ebedbe27ff507c683322ba44a264f7521aad7773f8125c |
