180 lines
8.3 KiB
Markdown
180 lines
8.3 KiB
Markdown
# Stable Diffusion web UI
|
|
A browser interface based on Gradio library for Stable Diffusion.
|
|
|
|
Original script with Gradio UI was written by a kind anonymous user. This is a modification.
|
|
|
|
|
|
## Installing and running
|
|
|
|
### Stable Diffusion
|
|
|
|
This script assumes that you already have main Stable Diffusion sutff installed, assumed to be in directory `/sd`.
|
|
If you don't have it installed, follow the guide:
|
|
|
|
- https://rentry.org/kretard
|
|
|
|
This repository's `webgui.py` is a replacement for `kdiff.py` from the guide.
|
|
|
|
Particularly, following files must exist:
|
|
|
|
- `/sd/configs/stable-diffusion/v1-inference.yaml`
|
|
- `/sd/models/ldm/stable-diffusion-v1/model.ckpt`
|
|
- `/sd/ldm/util.py`
|
|
- `/sd/k_diffusion/__init__.py`
|
|
|
|
### GFPGAN
|
|
|
|
If you want to use GFPGAN to improve generated faces, you need to install it separately.
|
|
Follow instructions from https://github.com/TencentARC/GFPGAN, but when cloning it, do so into Stable Diffusion main directory, `/sd`.
|
|
After that download [GFPGANv1.3.pth](https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth) and put it
|
|
into the `/sd/GFPGAN/experiments/pretrained_models` directory. If you're getting troubles with GFPGAN support, follow instructions
|
|
from the GFPGAN's repository until `inference_gfpgan.py` script works.
|
|
|
|
The following files must exist:
|
|
|
|
- `/sd/GFPGAN/inference_gfpgan.py`
|
|
- `/sd/GFPGAN/experiments/pretrained_models/GFPGANv1.3.pth`
|
|
|
|
If the GFPGAN directory does not exist, you will not get the option to use GFPGAN in the UI. If it does exist, you will either be able
|
|
to use it, or there will be a message in console with an error related to GFPGAN.
|
|
|
|
### Web UI
|
|
|
|
Run the script as:
|
|
|
|
`python webui.py`
|
|
|
|
When running the script, you must be in the main Stable Diffusion directory, `/sd`. If you cloned this repository into a subdirectory
|
|
of `/sd`, say, the `stable-diffusion-webui` directory, you will run it as:
|
|
|
|
`python stable-diffusion-webui/webui.py`
|
|
|
|
When launching, you may get a very long warning message related to some weights not being used. You may freely ignore it.
|
|
After a while, you will get a message like this:
|
|
|
|
```
|
|
Running on local URL: http://127.0.0.1:7860/
|
|
```
|
|
|
|
Open the URL in browser, and you are good to go.
|
|
|
|
## Features
|
|
The script creates a web UI for Stable Diffusion's txt2img and img2img scripts. Following are features added
|
|
that are not in original script.
|
|
|
|
### GFPGAN
|
|
Lets you improve faces in pictures using the GFPGAN model. There is a checkbox in every tab to use GFPGAN at 100%, and
|
|
also a separate tab that just allows you to use GFPGAN on any picture, with a slider that controls how strongthe effect is.
|
|
|
|
|
|
|
|
### Sampling method selection
|
|
Pick out of three sampling methods for txt2img: DDIM, PLMS, k-diffusion:
|
|
|
|
|
|
|
|
### Prompt matrix
|
|
Separate multiple prompts using the `|` character, and the system will produce an image for every combination of them.
|
|
For example, if you use `a busy city street in a modern city|illustration|cinematic lighting` prompt, there are four combinations possible (first part of prompt is always kept):
|
|
|
|
- `a busy city street in a modern city`
|
|
- `a busy city street in a modern city, illustration`
|
|
- `a busy city street in a modern city, cinematic lighting`
|
|
- `a busy city street in a modern city, illustration, cinematic lighting`
|
|
|
|
Four images will be produced, in this order, all with same seed and each with corresponding prompt:
|
|
|
|
|
|
Another example, this time with 5 prompts and 16 variations:
|
|
|
|
|
|
If you use this feature, batch count will be ignored, because the number of pictures to produce
|
|
depends on your prompts, but batch size will still work (generating multiple pictures at the
|
|
same time for a small speed boost).
|
|
|
|
### Flagging
|
|
Click the Flag button under the output section, and generated images will be saved to `log/images` directory, and generation parameters
|
|
will be appended to a csv file `log/log.csv` in the `/sd` directory.
|
|
|
|
> but every image is saved, why would I need this?
|
|
|
|
If you're like me, you experiment a lot with prompts and settings, and only few images are worth saving. You can
|
|
just save them using right click in browser, but then you won't be able to reproduce them later because you will not
|
|
know what exact prompt created the image. If you use the flag button, generation paramerters will be written to csv file,
|
|
and you can easily find parameters for an image by searching for its filename.
|
|
|
|
### Copy-paste generation parameters
|
|
A text output provides generation parameters in an easy to copy-paste form for easy sharing.
|
|
|
|
|
|
|
|
If you generate multiple pictures, the displayed seed will be the seed of the first one.
|
|
|
|
### Correct seeds for batches
|
|
If you use a seed of 1000 to generate two batches of two images each, four generated images will have seeds: `1000, 1001, 1002, 1003`.
|
|
Previous versions of the UI would produce `1000, x, 1001, x`, where x is an iamge that can't be generated by any seed.
|
|
|
|
### Resizing
|
|
There are three options for resizing input images in img2img mode:
|
|
|
|
- Just resize - simply resizes source image to target resolution, resulting in incorrect aspect ratio
|
|
- Crop and resize - resize source image preserving aspect ratio so that entirety of target resolution is occupied by it, and crop parts that stick out
|
|
- Resize and fill - resize source image preserving aspect ratio so that it entirely fits target resolution, and fill empty space by rows/columns from source image
|
|
|
|
Example:
|
|
|
|
|
|
### Loading
|
|
Gradio's loading graphic has a very negative effect on the processing speed of the neural network.
|
|
My RTX 3090 makes images about 10% faster when the tab with gradio is not active. By default, the UI
|
|
now hides loading progress animation and replaces it with static "Loading..." text, which achieves
|
|
the same effect. Use the `--no-progressbar-hiding` commandline option to revert this and show loading animations.
|
|
|
|
### Prompt validation
|
|
Stable Diffusion has a limit for input text length. If your prompt is too long, you will get a
|
|
warning in the text output field, showing which parts of your text were truncated and ignored by the model.
|
|
|
|
### Loopback
|
|
A checkbox for img2img allowing to automatically feed output image as input for the next batch. Equivalent to
|
|
saving output image, and replacing input image with it. Batch count setting controls how many iterations of
|
|
this you get.
|
|
|
|
Usually, when doing this, you would choose one of many images for the next iteration yourself, so the usefulness
|
|
of this feature may be questionable, but I've managed to get some very nice outputs with it that I wasn't abble
|
|
to get otherwise.
|
|
|
|
Example: (cherrypicked result; original picture by anon)
|
|
|
|
|
|
|
|
### Png info
|
|
Adds information about generation parameters to PNG as a text chunk. You
|
|
can view this information later using any software that supports viewing
|
|
PNG chunk info, for example: https://www.nayuki.io/page/png-file-chunk-inspector
|
|
|
|
|
|
|
|
### Textual Inversion
|
|
Allows you to use pretrained textual inversion embeddings.
|
|
See originial site for details: https://textual-inversion.github.io/.
|
|
I used lstein's repo for training embdedding: https://github.com/lstein/stable-diffusion; if
|
|
you want to train your own, I recommend following the guide on his site.
|
|
|
|
No additional libraries/repositories are required to use pretrained embeddings.
|
|
|
|
To make use of pretrained embeddings, create `embeddings` directory in the root dir of Stable
|
|
Diffusion and put your embeddings into it. They must be .pt files about 5Kb in size, each with only
|
|
one trained embedding, and the filename (without .pt) will be the term you'd use in prompt
|
|
to get that embedding.
|
|
|
|
As an example, I trained one for about 5000 steps: https://files.catbox.moe/e2ui6r.pt; it does
|
|
not produce very good results, but it does work. Download and rename it to `Usada Pekora.pt`,
|
|
and put it into `embeddings` dir and use Usada Pekora in prompt.
|
|
|
|
|
|
|
|
### Settings
|
|
A tab with settings, allowing you to use UI to edit more than half of parameters that previously
|
|
were commandline. Settings are saved to config.js file. Settings that remain as commandline
|
|
options are ones that are required at startup.
|