ImaginAIry

AI imagined images.

>> pip install imaginairy

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

Features

• It makes images from text descriptions!
• Generate images either in code or from command line.
• It just works (if you have the right hardware)
• Noisy logs are gone (which was surprisingly hard to accomplish)
• WeightedPrompts let you smash together separate prompts ()

How To

from imaginairy import imagine_images, imagine_image_files, ImaginePrompt, WeightedPrompt

prompts = [
    ImaginePrompt("a scenic landscape", seed=1),
    ImaginePrompt("a bowl of fruit"),
    ImaginePrompt([
       WeightedPrompt("cat", weight=1),
       WeightedPrompt("dog", weight=1),
    ])
]
for result in imagine_images(prompts):
    # do something
    result.save("my_image.jpg")
    
# or

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

Requirements

• Computer with CUDA supported graphics card. ~10 gb video ram OR
• Apple M1 computer

Improvements from CompVis

• img2img actually does # of steps you specify

Models Used

• CLIP
• LDM - Latent Diffusion
• Stable Diffusion - https://github.com/CompVis/stable-diffusion

Todo

• add safety model - https://github.com/CompVis/stable-diffusion/blob/main/scripts/txt2img.py#L21-L28
• add docs
• deploy to pypi
• add tests
• set up ci (test/lint/format)
• remove yaml config
• performance optimizations https://github.com/huggingface/diffusers/blob/main/docs/source/optimization/fp16.mdx
• Interface improvements
  • init-image at command line
  • prompt expansion?
  • webserver interface (low priority, this is a library)
• Image Generation Features
  • image describe feature
  • outpainting
  • inpainting
  • face improvements
  • upscaling
  • cross-attention control:
    • https://github.com/bloc97/CrossAttentionControl/blob/main/CrossAttention_Release_NoImages.ipynb
  • tiling
  • output show-work videos
  • zooming videos? a la disco diffusion