ImaginAIry

7.8k 415

04 May, 2024

Python

What is ImaginAIry ?

AI imagined images. Pythonic generation of stable diffusion images and videos that “just works” on Linux and macOS(M1) (and sometimes windows).

# on macOS, make sure rust is installed first

# be sure to use Python 3.10, Python 3.11 is not supported at the moment

>> pip install imaginairy

>> imagine "a scenic landscape" "a photo of a dog" "photo of a fruit bowl" "portrait photo of a freckled woman" "a bluejay"

# Make an AI video

>> aimg videogen --start-image rocket.png

How To

For full command line instructions run aimg --help

from imaginairy import imagine, imagine_image_files, ImaginePrompt, WeightedPrompt, LazyLoadingImage

url = "https://upload.wikimedia.org/wikipedia/commons/thumb/6/6c/Thomas_Cole_-_Architect%E2%80%99s_Dream_-_Google_Art_Project.jpg/540px-Thomas_Cole_-_Architect%E2%80%99s_Dream_-_Google_Art_Project.jpg?raw=true"

prompts = [

    ImaginePrompt("a scenic landscape", seed=1, upscale=True),

    ImaginePrompt("a bowl of fruit"),

    ImaginePrompt([

        WeightedPrompt("cat", weight=1),

        WeightedPrompt("dog", weight=1),

    ]),

    ImaginePrompt(

        "a spacious building",

        init_image=LazyLoadingImage(url=url)

    ),

    ImaginePrompt(

        "a bowl of strawberries",

        init_image=LazyLoadingImage(filepath="mypath/to/bowl_of_fruit.jpg?raw=true"),

        mask_prompt="fruit OR stem{*2}",  # amplify the stem mask x2

        mask_mode="replace",

        mask_modify_original=True,

    ),

    ImaginePrompt("strawberries", tile_mode=True),

]

for result in imagine(prompts):

    # do something

    result.save("my_image.jpg?raw=true")

# or

imagine_image_files(prompts, outdir="./my-art")

Requirements

~10 gb space for models to download
A CUDA supported graphics card with >= 11gb VRAM (and CUDA installed) or an M1 processor.
Python installed. Preferably Python 3.10. (not conda)
For macOS rust and setuptools-rust must be installed to compile the tokenizer library.

They can be installed via: curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh and pip install setuptools-rust

Running in Docker

See example Dockerfile (works on machine where you can pass the gpu into the container)

docker build . -t imaginairy

# you really want to map the cache or you end up wasting a lot of time and space redownloading the model weights

docker run -it --gpus all -v $HOME/.cache/huggingface:/root/.cache/huggingface -v $HOME/.cache/torch:/root/.cache/torch -v `pwd`/outputs:/outputs imaginairy /bin/bash

Running on Google Colab

Example Colab