https://github.com/joehalliwell/paraphernalia

An assortment of tools for making digital art.
https://github.com/joehalliwell/paraphernalia

art artificial-intelligence

Last synced: 14 days ago
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An assortment of tools for making digital art.

• Host: GitHub
• URL: https://github.com/joehalliwell/paraphernalia
• Owner: joehalliwell
• License: gpl-3.0
• Created: 2021-04-01T07:08:41.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-01-02T00:04:52.000Z (12 months ago)
• Last Synced: 2024-01-02T19:33:08.080Z (12 months ago)
• Topics: art, artificial-intelligence
• Language: Python
• Homepage: https://joehalliwell.com/paraphernalia
• Size: 2.5 MB
• Stars: 0
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Paraphernalia

[![CI Badge](https://github.com/joehalliwell/paraphernalia/actions/workflows/test.yml/badge.svg)](https://github.com/joehalliwell/paraphernalia/actions)

[![CI Badge](https://github.com/joehalliwell/paraphernalia/actions/workflows/docs.yml/badge.svg)](https://github.com/joehalliwell/paraphernalia/actions)

An assortment of tools for making digital art from Joe Halliwell

(@joehalliwell).

## Features

- [Decent documentation](http://joehalliwell.com/paraphernalia)

- Fragment shader realtime preview and offline rendering

- CLIP-based image generation

- Helpers for running creative projects in jupyter/Colaboratory

## Quick start guide

In a notebook/Colaboratory:

```

!pip install --upgrade git+https://github.com/joehalliwell/paraphernalia.git[openai,taming]

import paraphernalia as pa

pa.setup()

```

For developers: `poetry install`

## TODOs

### General

- Add CLIP/generator sample notebook

- Oblique strategy of the day during startup

## review

- Move reviewed folders to a target folder "lost"

- "kept" and "lost" should excluded

- Notebook mode?

### glsl

- Support all/more Book of Shaders uniforms

- Support all Shadertoy uniforms (see https://github.com/iY0Yi/ShaderBoy)

- Support buffers

#### clip

- Is anti-prompt logic actually working?

- Adaptive focus

- Factor our perceptual modes

- Perceptual masking for CLIP

- Image prompts

- Add SRCNN

- Use https://github.com/assafshocher/ResizeRight

### torch

- Fix replace_grad and add tests

- Fix clamp_with_grad and add tests

- Add BigGAN generators

- Add soft_permutation()

- Add ZX Spectrum/C64 Standard Mode generator

- Main entry point for generator+CLIP?

- Add standard description string/slug to generators

- Add Diffusion generator