jagilley / stable-diffusion-depth2img

Create variations of an image while preserving shape and depth

  • Public
  • 53.2K runs
  • GitHub
  • License

Input

Output

Run time and cost

This model runs on Nvidia A100 (40GB) GPU hardware. Predictions typically complete within 19 seconds. The predict time for this model varies significantly based on the inputs.

Readme

Create variations of an image while preserving shape and depth.

This stable-diffusion-2-depth model is resumed from stable-diffusion-2-base (512-base-ema.ckpt) and finetuned for 200k steps. Added an extra input channel to process the (relative) depth prediction produced by MiDaS (dpt_hybrid) which is used as an additional conditioning.

  • Developed by: Robin Rombach, Patrick Esser
  • Model type: Diffusion-based text-to-image generation model
  • Language(s): English
  • License: CreativeML Open RAIL++-M License
  • Model Description: This is a model that can be used to generate and modify images based on text prompts. It is a Latent Diffusion Model that uses a fixed, pretrained text encoder (OpenCLIP-ViT/H).
  • Resources for more information: GitHub Repository.

Intended use

See stability-ai/stable-diffusion for direct use, misuse, malicious use, out-of-scope use, limitations, and bias.