onnx-web/docs/chain-pipelines.md

Chain Pipelines

Chain pipelines are a new feature in v0.6 that allows you to run any combination of models on images of almost any size, by automatically splitting them into smaller tiles as needed. Individual models are run on each tile, then the results are recombined and passed on to the next stage.

Contents

• Chain Pipelines
  • Contents
  • Overview
    • Format
  • Stages
    • Blending Stages
      • Blend: Denoise
      • Blend: Grid
      • Blend: Img2img
      • Blend: Linear
      • Blend: Mask
    • Correction Stages
      • Correct: CodeFormer
      • Correct: GFPGAN
    • Compound Stages
      • Highres Stage
      • Upscale Stage
    • Persistence Stages
      • Persist: Disk
      • Persist: S3
    • Reduction Stages
      • Reduce: Crop
      • Reduce: Thumbnail
    • Source Stages
      • Source: Noise
      • Source: S3
      • Source: Txt2img
      • Source: URL
    • Upscaling Stages
      • Upscale: BSRGAN
      • Upscale: Highres
      • Upscale: Outpaint
      • Upscale: Real ESRGAN
      • Upscale: Simple
      • Upscale: Stable Diffusion
      • Upscale: SwinIR

Overview

Format

The /api/chain endpoint accepts a chain pipeline in JSON format and adds it to the queue of background jobs.

Pipelines are defined mostly through their stages, where each stage specifies a function to be run and the parameters for that function, including the name of the model to be used.

The output of the pipeline will not automatically be saved to disk, which is the case for the single-stage endpoints. You must use at least one persist-* stage. Persist stages can be placed anywhere in the pipeline and can also save intermediate output, such as the result of a source-txt2img stage before upscaling it.

{
  "stages": [
    {
      "name": "start",
      "type": "source-txt2img",
      "params": {
        "prompt": "a magical wizard"
      }
    },
    {
      "name": "expand",
      "type": "upscale-outpaint",
      "params": {
        "border": 256,
        "prompt": "a magical wizard in a robe fighting a dragon"
      }
    },
    {
      "name": "save-local",
      "type": "persist-disk",
      "params": {
        "tiles": "hd8k"
      }
    }
  ]
}

The complete schema can be found in api/schema.yaml and some example pipelines are available in common/pipelines.

Stages

Blending Stages

Blend: Denoise

TODO

Blend: Grid

TODO

Blend: Img2img

TODO

Blend: Linear

TODO

Blend: Mask

TODO

Correction Stages

Correct: CodeFormer

TODO

Correct: GFPGAN

TODO

Compound Stages

Not currently available through JSON API.

Highres Stage

TODO

Upscale Stage

TODO

Persistence Stages

Persist: Disk

TODO

Persist: S3

TODO

Reduction Stages

Reduce: Crop

TODO

Reduce: Thumbnail

TODO

Source Stages

Source: Noise

TODO

Source: S3

TODO

Source: Txt2img

TODO

Source: URL

TODO

Upscaling Stages

Upscale: BSRGAN

TODO

Upscale: Highres

TODO

Upscale: Outpaint

Upscaling stage using outpainting. This adds empty borders to the source image, optionally fills them with noise, and then runs inpainting on those areas.

Upscale: Real ESRGAN

Upscaling stage using the Real ESRGAN upscaling models, available in x2 and x4 versions:

• https://github.com/xinntao/Real-ESRGAN/releases

Upscale: Simple

TODO

Upscale: Stable Diffusion

Upscaling stage using the Stable Diffusion x4 upscaling model:

• https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler
• https://huggingface.co/ssube/stable-diffusion-x4-upscaler-onnx

Upscale: SwinIR

TODO