The image-to-image pipeline of the AI Subnet enables advanced image manipulations including style transfer, image enhancement, and more. This pipeline leverages cutting-edge diffusion models from the HuggingFace image-to-image pipeline.


Warm Models

The current warm model requested for the image-to-image pipeline is:

  • timbrooks/instruct-pix2pix: A powerful diffusion model that edits images to a high-quality standard based on human-written instructions

For faster responses with different image-to-image diffusion models, ask Orchestrators to load it on their GPU via the ai-video channel in Discord Server.

On-Demand Models

The following models have been tested and verified for the image-to-image pipeline:

If a specific model you wish to use is not listed, please submit a feature request on GitHub to get the model verified and added to the list.

Basic Usage Instructions

For a detailed understanding of the image-to-image endpoint and to experiment with the API, see the AI Subnet API Reference.

To generate an image with the image-to-image pipeline, send a POST request to the Gateway’s image-to-image API endpoint:

curl -X POST https://<gateway-ip>/image-to-image \
    -F model_id="ByteDance/SDXL-Lightning" \
    -F image=@<PATH_TO_IMAGE>/cool-cat.png \
    -F prompt="a hat"

In this command:

  • <gateway-ip> should be replaced with your AI Gateway’s IP address.
  • model_id is the diffusion model for image generation.
  • The image field holds the absolute path to the image file to be transformed.
  • prompt is the text description for the image.

For additional optional parameters, refer to the AI Subnet API Reference.

After execution, the Orchestrator processes the request and returns the response to the Gateway:

  "images": [
      "nsfw": false,
      "seed": 3197613440,
      "url": "https://<gateway-ip>/stream/dd5ad78d/7adde483.png"

The url in the response is the URL of the generated image. Download the image with:

curl -O "https://<STORAGE_ENDPOINT>/stream/dd5ad78d/7adde483.png"

API Reference

API Reference

Explore the image-to-image endpoint and experiment with the API in the AI Subnet API Reference.