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https://github.com/danielenricocahall/glide-text2im

GLIDE: a diffusion-based text-conditional image synthesis model

https://github.com/danielenricocahall/glide-text2im

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GLIDE: a diffusion-based text-conditional image synthesis model

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  • Host: GitHub
  • Owner: danielenricocahall
  • License: mit
  • Default Branch: main
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  • Size: 1.94 MB
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Fork of openai/glide-text2im
Created over 4 years ago · Last pushed over 4 years ago

https://github.com/danielenricocahall/glide-text2im/blob/main/ 

# GLIDE

This is the official codebase for running the small, filtered-data GLIDE model from [GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models](https://arxiv.org/abs/2112.10741).

For details on the pre-trained models in this repository, see the [Model Card](model-card.md).

# Usage

To install this package, clone this repository and then run:

```
pip install -e .
```

For detailed usage examples, see the [notebooks](notebooks) directory.

 * The [text2im](notebooks/text2im.ipynb) [![][colab]][colab-text2im] notebook shows how to use GLIDE (filtered) with classifier-free guidance to produce images conditioned on text prompts. 
 * The [inpaint](notebooks/inpaint.ipynb) [![][colab]][colab-inpaint] notebook shows how to use GLIDE (filtered) to fill in a masked region of an image, conditioned on a text prompt. 
 * The [clip_guided](notebooks/clip_guided.ipynb) [![][colab]][colab-guided] notebook shows how to use GLIDE (filtered) + a filtered noise-aware CLIP model to produce images conditioned on text prompts. 

[colab]: 
[colab-text2im]: 
[colab-inpaint]: 
[colab-guided]:

Owner

  • Name: Danny
  • Login: danielenricocahall
  • Kind: user
  • Location: Philadelphia, PA
  • Company: Disney Streaming Services

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