Metadata-Version: 2.1
Name: soifunc
Version: 0.1.0
Summary: Soichiro's VapourSynth Functions Collection
License: MIT
Author: Josh Holmer
Author-email: jholmer.in@gmail.com
Requires-Python: >=3.10,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: vapoursynth (>=60)
Requires-Dist: vsdeband (>=0.7.2)
Description-Content-Type: text/markdown

## soifunc

Vapoursynth scripts that might be useful to someone

### Installation

#### Arch Linux

Install from [AUR](https://aur.archlinux.org/packages/vapoursynth-plugin-soifunc-git)

#### Other

First install the required plugins which are not available in pip:

- [neo_f3kdb](https://github.com/HomeOfAviSynthPlusEvolution/neo_f3kdb)
- [kagefunc](https://github.com/Irrational-Encoding-Wizardry/kagefunc)
- [muvsfunc](https://github.com/WolframRhodium/muvsfunc)
- [mvsfunc](https://github.com/HomeOfVapourSynthEvolution/mvsfunc)
- [znedi3](https://github.com/sekrit-twc/znedi3)
- [nnedi3_resample](https://github.com/HomeOfVapourSynthEvolution/nnedi3_resample)
- [BM3DCUDA](https://github.com/WolframRhodium/VapourSynth-BM3DCUDA)

Install from pip:

```bash
pip install soifunc
```

Or the latest git version:

```bash
pip install git+https://github.com/shssoichiro/soifunc.git
```

### Usage

Any of the functions will require an `import soifunc` prior to where they are used.

#### GoodResize

`clip = soifunc.GoodResize(clip, 1920, 1080)`

Resizes a clip to the specified dimensions using a high quality method.

For upscaling, luma is resized using `nnedi3_resample`.

For downscaling, luma is resized using `SSIM_downsample`.

Chroma is always resized using `Spline36`.

**If this filter causes your video to produce a blank output**, see this issue: https://github.com/HomeOfVapourSynthEvolution/VapourSynth-TCanny/issues/14

#### RetinexDeband

`clip = soifunc.RetinexDeband(clip, threshold = 16 [, showmask = False])`

High quality debanding using a retinex mask, designed to preserve details in both light and dark areas.

`threshold` controls debanding strength. `16` is a reasonable starting point. Increase as needed until satisfied.

`showmask` is an optional debugging parameter, setting this to `True` will output the mask that will be used to preserve edges.

Note that this debander does not automatically add grain.
If you need to add grain before encoding, use `kagefunc.adaptive_grain`.
If you're using AV1 grain synthesis, you _do not_ need to add grain before encoding.

#### ClipLimited

`clip = soifunc.ClipLimited(clip)`

Compression introduces rounding errors and whatnot that can lead
to some pixels in your source being outside the range of
valid Limited range values. These are clamped to the valid
range by the player on playback, but that means we can save
a small amount of bitrate if we clamp them at encode time.
This function does that.

Recommended to use at the very end of your filter chain,
in the final encode bit depth.

#### BM3DCUDA Wrappers

See [BM3DCUDA](https://github.com/WolframRhodium/VapourSynth-BM3DCUDA) for list of args.

`clip = soifunc.BM3DCPU(clip, ...args)`

`clip = soifunc.BM3DCuda(clip, ...args)`

`clip = soifunc.BM3DCuda_RTC(clip, ...args)`

Provides wrappers around the accelerated BM3D functions in BM3DCUDA, similar to the wrapper provided for the base BM3D plugin in mvsfunc.
These functions perform all necessary colorspace conversion, so they are considerably simpler to use than manually calling BM3DCuda.

#### MCDenoise

Applies motion compensation to a denoised clip to improve detail preservation.
Credit to Clybius for creating this code.

Example usage:

```python
import soifunc
import dfttest2
import functools    # functools is built in to python
denoiser = functools.partial(dfttest2.DFTTest, sigma=1.5, backend=dfttest2.Backend.CPU)
clip = soifunc.MCDenoise(clip, denoiser)
```

Params:

- `denoiser`: A function defining how to denoise the motion-compensated frames.
  Denoiser params can be added using `functools.partial`.
- `prefilter`: An optional prefiltered input clip to enable better searching for motion vectors

