README.md

BunnyNet AI

Generating images with Bunny AI.

Introduction

On December 15th, 2022 BunnyWay introduced Bunny AI: an easy way to dynamically generate images using AI technology such as DALL-E 2 and Stable Diffusion

In order to make it easier to generate images for developers, this (python) application will simply send batch requests based on user's input.

Note:

• This is a non-official library for Bunny AI.

Setup

• You can choose to either follow the Docker or Python route.
• For help, run main.py -h.
• Images are always saved in the ./output directory (relative to the working directory).
  • In the docker container this will be /app/output.

🐋 Docker / Compose

Docker

1. Pull the image t0shy/bunnynet-ai:latest.

docker pull t0shy/bunnynet-ai:latest

or build from source.

docker build -t t0shy/bunnynet-ai:latest --no-cache .

2. Run it.

docker run -it --rm -v ${PWD}/output:/app/output t0shy/bunnynet-ai:latest python3 main.py -k "489eb71e-1259-4e1a-83c2-2d7859eec469" -hn "myzone.b-cdn.net" -p "cute pixel art of a bunny with a colorful solid background" -n 5 -v

Docker Compose

1. Create a docker-compose.yml.

version: '3.9'

services:
  bunnynet-ai:
    image: t0shy/bunnynet-ai:latest
    volumes:
      - ./output/:/app/output

2. Up the service.

docker compose up -d --remove-orphans

3. Run it.

docker compose run --rm bunnynet-ai python main.py -k "489eb71e-1259-4e1a-83c2-2d7859eec469" -hn "myzone.b-cdn.net" -p "cute pixel art of a bunny with a colorful solid background" -n 5 -v

4. Saved images can be found on the mounted directory of the host machine.
   • Filename format is as follows: [{image_blueprint}]{slug_prompt}-{seed}.{file_extension}.

🐍 Python

1. Install the requirements with pip.

pip install -r requirements.txt

2. Run it.

python main.py -k "489eb71e-1259-4e1a-83c2-2d7859eec469" -hn "myzone.b-cdn.net" -p "cute pixel art of a bunny with a colorful solid background" -n 5 -v

3. Saved images can be found in the ./output directory (relative to working directory).
   • Filename format is as follows: [{image_blueprint}]{slug_prompt}-{seed}.{file_extension}.

🛠️ Contribute

Prerequisites

• Docker Compose
  • See the Docker Compose installation guide to get started.
• Task
  • See the Task installation guide to get started

Pre-commit

Setting up pre-commit code style & quality checks for local development.

pre-commit install

Checks

task contribute

Note: you can use task tools:black:fix to resolve codestyle issues.

❕ License

This repository comes with the MIT license.