FeMaSR
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors, based on https://github.com/chaofengc/FeMaSR.
Dependencies
- PyTorch 2.4.0.dev or later
- VapourSynth R66 or later
trt requires additional Python packages:
- TensorRT 10.0.1
- Torch-TensorRT 2.4.0.dev
To install TensorRT, run pip install tensorrt==10.0.1 tensorrt-cu12_bindings==10.0.1 tensorrt-cu12_libs==10.0.1 --extra-index-url https://pypi.nvidia.com
To install Torch-TensorRT, Windows users can pip install the whl file on Releases. Linux users can run pip install --pre torch_tensorrt --index-url https://download.pytorch.org/whl/nightly/cu124 (requires PyTorch nightly build).
Installation
pip install -U vsfemasr
python -m vsfemasr
Usage
from vsfemasr import femasr
ret = femasr(clip)
See __init__.py for the description of the parameters.
1 maintainer
Metadata
1 maintainer
Release files for vsfemasr 2.0.0
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| vsfemasr-2.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Release files / vsfemasr-2.0.0-py3-none-any.whl
| Download URL | vsfemasr-2.0.0-py3-none-any.whl |
|---|---|
| Size | 22.6 kB |
| Tags | Python 3 |
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