apextoaster
/
onnx-web
1
0
Fork 0
Code Actions

chore(docs): explain upscale, correction, and highres parameters

This commit is contained in:
Sean Sube 2023-06-22 22:55:03 -05:00
parent ca2e436f06
commit 7a8184a5da
Signed by: ssube
GPG Key ID: 3EED7B957D362AF1
2 changed files with 145 additions and 41 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

185
docs/user-guide.md
View File

@ -35,7 +35,6 @@ Please see [the server admin guide](server-admin.md) for details on how to confi
- [CLIP skip tokens](#clip-skip-tokens)
- [Long prompt weighting syntax](#long-prompt-weighting-syntax)
- [Pipelines](#pipelines)
- [Stable Diffusion pipeline](#stable-diffusion-pipeline)
- [ControlNet pipeline](#controlnet-pipeline)
- [img2img pipeline](#img2img-pipeline)
- [Inpaint pipeline](#inpaint-pipeline)
@ -60,6 +59,11 @@ Please see [the server admin guide](server-admin.md) for details on how to confi
- [Negative prompt parameter](#negative-prompt-parameter)
- [Width and height parameters](#width-and-height-parameters)
- [Highres parameters](#highres-parameters)
- [Highres steps parameter](#highres-steps-parameter)
- [Highres scale parameter](#highres-scale-parameter)
- [Highres strength parameter](#highres-strength-parameter)
- [Highres upscaler parameter](#highres-upscaler-parameter)
- [Highres iterations parameter](#highres-iterations-parameter)
- [Upscale and correction parameters](#upscale-and-correction-parameters)
- [Img2img tab](#img2img-tab)
- [Img2img source image](#img2img-source-image)
@ -71,10 +75,12 @@ Please see [the server admin guide](server-admin.md) for details on how to confi
- [Noise source parameter](#noise-source-parameter)
- [Outpaint parameters](#outpaint-parameters)
- [Upscale tab](#upscale-tab)
- [Scale parameter](#scale-parameter)
- [Outscale parameter](#outscale-parameter)
- [Denoise parameter](#denoise-parameter)
- [Face correction and strength](#face-correction-and-strength)
- [Upscale scale parameter](#upscale-scale-parameter)
- [Upscale outscale parameter](#upscale-outscale-parameter)
- [Upscale denoise parameter](#upscale-denoise-parameter)
- [Correction strength parameter](#correction-strength-parameter)
- [Correction outscale parameter](#correction-outscale-parameter)
- [Correction order parameter](#correction-order-parameter)
- [Blend tab](#blend-tab)
- [Models tab](#models-tab)
- [Settings tab](#settings-tab)
@ -189,13 +195,15 @@ The models used by ONNX web are split up into four groups:
2. specialized models like [Knollingcase](https://huggingface.co/Aybeeceedee/knollingcase) or
[OpenJourney](https://huggingface.co/prompthero/openjourney)
2. Upscaling
1. [Real ESRGAN](https://github.com/xinntao/Real-ESRGAN)
2. [Stable Diffusion](https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler)
1. [BSRGAN](https://github.com/cszn/BSRGAN)
2. [Real ESRGAN](https://github.com/xinntao/Real-ESRGAN)
3. [Stable Diffusion](https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler)
4. [SwinIR](https://github.com/JingyunLiang/SwinIR)
3. Correction
1. [CodeFormer](https://github.com/sczhou/CodeFormer)
2. [GFPGAN](https://github.com/TencentARC/GFPGAN)
4. Networks
1. [LoRA](https://arxiv.org/abs/2106.09685)
1. [LoRA](https://arxiv.org/abs/2106.09685) and [LyCORIS](https://github.com/KohakuBlueleaf/LyCORIS)
2. [Textual Inversion](https://textual-inversion.github.io/)
There are many other models available and specialized variations for anime, TV shows, and all sorts of other styles. You
@ -310,8 +318,16 @@ Keywords:
Examples:
- 4k, hdr, smooth, sharp focus, high resolution, photorealistic, detailed
- 8k, HDR, shallow depth of field, broad light, high contrast, backlighting, bloom, light sparkles, chromatic aberration, sharp focus, RAW color photo
- 4k, HDR, smooth, sharp focus, high resolution, photorealistic, detailed
- 8k, HDR, shallow depth of field, broad light, high contrast, backlighting, bloom, light sparkles, chromatic
aberration, sharp focus, RAW color photo
Links:
- https://stable-diffusion-art.com/how-to-come-up-with-good-prompts-for-ai-image-generation
- https://contentwritertools.com/stable-diffusion-prompt-guide
- https://www.klartai.com/post/best-stable-diffusion-midjourney-prompt-a-comprehensive-guide-to-text-to-image-generation
- https://getimg.ai/guides/guide-to-negative-prompts-in-stable-diffusion
### Prompt tokens
@ -422,41 +438,63 @@ long prompt weighting syntax.
If you select a pipeline that is not valid for the current tab, the default pipeline for that tab will be used instead.
### Stable Diffusion pipeline
TODO
### ControlNet pipeline
The ControlNet pipeline
The ControlNet pipeline allows you to modify an existing image using the ControlNet filters and models found in the
img2img tab.
ControlNet is only valid for the img2img tab.
### img2img pipeline
TODO
The img2img pipeline allows you to modify an existing image using a text prompt.
Img2img is only valid for the img2img tab.
### Inpaint pipeline
TODO
The inpaint pipeline allows you to selectively replace sections of an existing image using a prompt.
Inpaint is only valid for the inpaint tab.
### Long prompt weighting pipeline
TODO
The long prompt weighting pipeline allows you to use [long prompt weighting syntax](#long-prompt-weighting-syntax) in
your prompt and emphasize some tokens over others.
Long prompt weighting is valid for the following tabs:
- txt2img
- img2img
- inpaint
### Panorama pipeline
TODO
The panorama pipeline allows you to generate and modify very large images.
Panorama is valid for the following tabs:
- txt2img
- img2img
- inpaint
### Instruct pix2pix pipeline
TODO
The instruct pix2pix pipelines allows you to modify an existing image using text instructions.
Instruct pix2pix is only valid for the img2img tab.
### Txt2Img pipeline
TODO
The txt2img pipeline allows you to generate an image from a text prompt.
Txt2img is only valid for the img2img tab.
### Upscale pipeline
TODO
The upscale pipeline is specifically for Stable Diffusion upscaling.
TODO: why is this special? when do you need to use it?
## Tabs
@ -509,23 +547,44 @@ Using -1 will generate a new seed on the server for each image.
#### Batch size parameter
TODO
The number of images to generate each time you press the generate button.
All of the images in the batch will share the same seed, and changing the batch size will change the results.
#### Tile size parameter
TODO
The size of each UNet tile when running [the panorama pipeline](#panorama-pipeline).
Increasing this is a lot like increasing the image size. It will produce larger areas with consistent shapes and
outlines, but will increase memory. Decreasing this too far can produce deep-fried results.
#### Overlap parameter
TODO
The amount that each highres and VAE tile should overlap.
Increasing this will increase the number of tiles and will take longer, but will reduce the strength of the seams
between tiles. Increasing this too far will cause blurry images.
- 0.25 is usually good for [highres](#highres-parameters)
- 0.5 is usually good for [panorama](#panorama-pipeline)
_Note:_ The highres and VAE overlap parameters may be split up in the future.
#### UNet stride parameter
TODO
The stride between UNet tiles when running [the panorama pipeline](#panorama-pipeline).
This behaves a lot like [the overlap parameter](#overlap-parameter) but only applies to the UNet when using [the
panorama pipeline](#panorama-pipeline).
_Note:_ This parameter may be combined with the overlap parameter in the future.
#### Tiled VAE parameter
TODO
Whether or not to use the tiled VAE.
The tiled VAE uses less memory and allows you to generate larger images, but may produce seams without enough
[overlap](#overlap-parameter).
#### Prompt parameter
@ -559,11 +618,46 @@ Controls the size of the output image, before upscaling.
#### Highres parameters
TODO
##### Highres steps parameter
The number of steps to use for each highres tile.
This is the same as [the steps parameter](#steps-parameter) in img2img. The number of steps that will actually run
is `steps * strength`, but a low number of steps (20-30) with moderate or high strength (0.5-1.0) will often produce
more duplicate shapes and totem pole style images.
##### Highres scale parameter
The output scale for [the highres upscaler](#highres-upscaler-parameter).
This is the same as [the upscale scale parameter](#upscale-scale-parameter).
##### Highres strength parameter
The blending strength for the highres img2img runs.
This is the same as [the img2img strength parameter](#strength-parameter).
##### Highres upscaler parameter
The upscaling method to be used for highres tiles.
- Bilinear is the fastest and produces moderate results, but usually needs more steps to correct the blur that has been
introduced
- Lanczos is reasonably fast and produces fairly good results, but requires more CPU than bilinear upscaling
- Upscaling uses your currently selected upscaling model and produces the best results, but can be very slow on CPU
##### Highres iterations parameter
The number of times to run highres.
The image will be resized by [the highres scale](#highres-scale-parameter) each iteration, so this is exponential: a
scale of 4 and 2 iterations will produce a final image that is 16 times the original size of the input image or
parameters. A scale of 2 and 3 iterations will produce a final image that is 8 times the original size.
#### Upscale and correction parameters
TODO: these allow you to use the upscale and face correction models with other pipelines
Please see [the upscale tab](#upscale-tab) for more details on the upscaling and correction parameters.
### Img2img tab
@ -677,32 +771,41 @@ without running a diffusion pipeline at all. This can be faster and avoids makin
Resize the output image before returning it to the client.
TODO: include other upscale models
This uses your currently selected [upscaling model](#model-and-network-types).
Enabling this will run Real ESRGAN and requires an upscaling model.
#### Upscale scale parameter
Check out [the Real ESRGAN Github](https://github.com/xinntao/Real-ESRGAN) for more details.
The trained output scale for the upscaling model.
#### Scale parameter
The final output size will be based on [the upscale outscale parameter](#upscale-outscale-parameter). Using a scale
larger than the outscale can produce a sharper image.
The output scale for Real ESRGAN. This output will be rescaled using the outscale parameter.
#### Upscale outscale parameter
#### Outscale parameter
The final output scale for the upscaling model.
The final output scale after running Real ESRGAN. This can increase _or_ decrease the size of the final
output. Lanczos interpolation is used when the outscale is greater than the scale.
This can increase _or_ decrease the size of the final output. Lanczos interpolation is used when the outscale is
greater than the scale, which can produce a blurry image.
#### Denoise parameter
#### Upscale denoise parameter
The amount of denoising to apply when using the RealESR x4 v4 model. Can be used to avoid over-smoothing the results.
#### Face correction and strength
#### Correction strength parameter
Run face correction the the output image before returning it to the client.
Enabling this will run GFPGAN and requires a correction model.
This uses your currently selected [correction model](#model-and-network-types).
Check out [the GFPGAN Github](https://github.com/TencentARC/GFPGAN) for more details.
#### Correction outscale parameter
The final output scale for the correction model.
This is a lot like [the upscale outscale parameter](#upscale-outscale-parameter).
#### Correction order parameter
TODO
### Blend tab

1
onnx-web.code-workspace
View File

@ -95,6 +95,7 @@
"upsample",
"upsampler",
"upsampling",
"upscaler",
"upscaling",
"venv",
"virtualenv",