mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
ec2dc24ad7
* Squashed commit of the following: commit82d9c25d9aAuthor: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 19:29:11 2022 +0200 fix branch name in mkdocs-flow commit2e276cecc1Author: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 19:28:35 2022 +0200 fix theme name commit2eb77c1173Author: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 19:14:42 2022 +0200 fixed some links and formating in main README commit66a7152e48Author: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 08:58:58 2022 +0200 trigger mkdocs deployment on main commit897cc373ceMerge:89da3713b5a830Author: Matthias Wild <40327258+mauwii@users.noreply.github.com> Date: Wed Sep 14 07:51:23 2022 +0200 Merge pull request #1 from mauwii/mkdocs Mkdocs commit3b5a8308ebAuthor: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 07:42:56 2022 +0200 huge update I was pretty busy trying to make the Readmes / docs look good in MkDocs commit0b4f5a926fAuthor: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 07:41:45 2022 +0200 update mkdocs config commit872172ea70Author: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 07:33:49 2022 +0200 added the mkdocs-git-revision-date-plugin commiteac81bf875Author: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 06:46:43 2022 +0200 add prettier config remove markdownlint move and rename requirements-mkdocs.txt commitb36d4cc088Author: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 02:06:39 2022 +0200 add dark theme commita14f18fedeAuthor: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 01:38:02 2022 +0200 update mkdocs flow and config commit2764b48693Author: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 01:15:33 2022 +0200 add mkdocs workflow commit1bd22523b1Author: mauwii <Mauwii@outlook.de> Date: Wed Sep 14 00:57:37 2022 +0200 I already begun with formating / revising the sites * change repository in mkdocs config to lstein * adapt changes from repos main README.md Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
100 lines
4.3 KiB
Markdown
100 lines
4.3 KiB
Markdown
---
|
|
title: Upscale
|
|
---
|
|
|
|
## **GFPGAN and Real-ESRGAN Support**
|
|
|
|
The script also provides the ability to do face restoration and upscaling with the help of GFPGAN
|
|
and Real-ESRGAN respectively.
|
|
|
|
As of version 1.14, environment.yaml will install the Real-ESRGAN package into the standard install
|
|
location for python packages, and will put GFPGAN into a subdirectory of "src" in the
|
|
stable-diffusion directory. (The reason for this is that the standard GFPGAN distribution has a
|
|
minor bug that adversely affects image color.) Upscaling with Real-ESRGAN should "just work" without
|
|
further intervention. Simply pass the --upscale (-U) option on the dream> command line, or indicate
|
|
the desired scale on the popup in the Web GUI.
|
|
|
|
For **GFPGAN** to work, there is one additional step needed. You will need to download and copy the
|
|
GFPGAN [models file](https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth)
|
|
into **src/gfpgan/experiments/pretrained_models**. On Mac and Linux systems, here's how you'd do it
|
|
using **wget**:
|
|
|
|
```bash
|
|
> wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth src/gfpgan/experiments/pretrained_models/
|
|
```
|
|
|
|
Make sure that you're in the stable-diffusion directory when you do this.
|
|
|
|
Alternatively, if you have GFPGAN installed elsewhere, or if you are using an earlier version of
|
|
this package which asked you to install GFPGAN in a sibling directory, you may use the
|
|
`--gfpgan_dir` argument with `dream.py` to set a custom path to your GFPGAN directory. _There are
|
|
other GFPGAN related boot arguments if you wish to customize further._
|
|
|
|
**Note: Internet connection needed:** Users whose GPU machines are isolated from the Internet (e.g.
|
|
on a University cluster) should be aware that the first time you run dream.py with GFPGAN and
|
|
Real-ESRGAN turned on, it will try to download model files from the Internet. To rectify this, you
|
|
may run `python3 scripts/preload_models.py` after you have installed GFPGAN and all its
|
|
dependencies.
|
|
|
|
## **Usage**
|
|
|
|
You will now have access to two new prompt arguments.
|
|
|
|
### **Upscaling**
|
|
|
|
`-U : <upscaling_factor> <upscaling_strength>`
|
|
|
|
The upscaling prompt argument takes two values. The first value is a scaling factor and should be
|
|
set to either `2` or `4` only. This will either scale the image 2x or 4x respectively using
|
|
different models.
|
|
|
|
You can set the scaling stength between `0` and `1.0` to control intensity of the of the scaling.
|
|
This is handy because AI upscalers generally tend to smooth out texture details. If you wish to
|
|
retain some of those for natural looking results, we recommend using values between `0.5 to 0.8`.
|
|
|
|
If you do not explicitly specify an upscaling_strength, it will default to 0.75.
|
|
|
|
### **Face Restoration**
|
|
|
|
`-G : <gfpgan_strength>`
|
|
|
|
This prompt argument controls the strength of the face restoration that is being applied. Similar to
|
|
upscaling, values between `0.5 to 0.8` are recommended.
|
|
|
|
You can use either one or both without any conflicts. In cases where you use both, the image will be
|
|
first upscaled and then the face restoration process will be executed to ensure you get the highest
|
|
quality facial features.
|
|
|
|
`--save_orig`
|
|
|
|
When you use either `-U` or `-G`, the final result you get is upscaled or face modified. If you want
|
|
to save the original Stable Diffusion generation, you can use the `-save_orig` prompt argument to
|
|
save the original unaffected version too.
|
|
|
|
### **Example Usage**
|
|
|
|
```bash
|
|
dream> superman dancing with a panda bear -U 2 0.6 -G 0.4
|
|
```
|
|
|
|
This also works with img2img:
|
|
|
|
```bash
|
|
dream> a man wearing a pineapple hat -I path/to/your/file.png -U 2 0.5 -G 0.6
|
|
```
|
|
|
|
### **Note**
|
|
|
|
GFPGAN and Real-ESRGAN are both memory intensive. In order to avoid crashes and memory overloads
|
|
during the Stable Diffusion process, these effects are applied after Stable Diffusion has completed
|
|
its work.
|
|
|
|
In single image generations, you will see the output right away but when you are using multiple
|
|
iterations, the images will first be generated and then upscaled and face restored after that
|
|
process is complete. While the image generation is taking place, you will still be able to preview
|
|
the base images.
|
|
|
|
If you wish to stop during the image generation but want to upscale or face restore a particular
|
|
generated image, pass it again with the same prompt and generated seed along with the `-U` and `-G`
|
|
prompt arguments to perform those actions.
|