5.2 KiB
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
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
Run fast non-local means denoising using cv2
.
Blend: Grid
Combine the source images into a grid.
Blend: Img2img
Run an img2img pipeline.
Blend: Linear
Blend two images using linear interpolation (0.0 is the first image, 1.0 is the second).
Blend: Mask
Blend two images using a mask.
Correction Stages
Correct: CodeFormer
Run correction using CodeFormer.
Correct: GFPGAN
Run correction using GFPGAN.
Compound Stages
Not currently available through JSON API.
Highres Stage
Prep one or more highres iterations. Each iteration is an upscale stage followed by img2img.
Upscale Stage
Prep upscale and correction stages.
Persistence Stages
Persist: Disk
Save all of the sources to disk.
Persist: S3
Save all of the sources to an S3 bucket.
Reduction Stages
Reduce: Crop
Crop a section out of each source.
Reduce: Thumbnail
Downscale each image into a thumbnail of itself.
Source Stages
Source: Noise
Create a new source using a noise generator.
Source: S3
Load a new source from an S3 bucket.
Source: Txt2img
Run a txt2img pipeline.
Source: URL
Load a new source from a URL.
Upscaling Stages
Upscale: BSRGAN
Upscaling stage using BSRGAN.
Upscale: Highres
Upscaling stage using highres.
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:
Upscale: Simple
Upscaling stage using bilinear or Lanczos upscaling.
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
Upscaling stage using SwinIR.