Postprocessing#
Intro#
This extension provides the ability to restore faces and upscale images.
Face restoration and upscaling can be applied at the time you generate the images, or at any later time against a previously-generated PNG file, using the !fix command. Outpainting and outcropping can only be applied after the fact.
Face Fixing#
The default face restoration module is GFPGAN. The default upscale is Real-ESRGAN. For an alternative face restoration module, see CodeFormer Support below.
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 InvokeAI directory. Upscaling with Real-ESRGAN
should "just work" without further intervention. Simply pass the --upscale
(-U) option on the invoke> command line, or indicate the desired scale on
the popup in the Web GUI.
GFPGAN requires a series of downloadable model files to work. These are
loaded when you run invokeai-configure. If GFPAN is failing with an
error, please run the following from the InvokeAI directory:
If you do not run this script in advance, the GFPGAN module will attempt to download the models files the first time you try to perform facial reconstruction.
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 : <facetool_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#
This also works with img2img:
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.
CodeFormer Support#
This repo also allows you to perform face restoration using CodeFormer.
In order to setup CodeFormer to work, you need to download the models like with
GFPGAN. You can do this either by running invokeai-configure or by manually
downloading the
model file
and saving it to ldm/invoke/restoration/codeformer/weights folder.
You can use -ft prompt argument to swap between CodeFormer and the default
GFPGAN. The above mentioned -G prompt argument will allow you to control the
strength of the restoration effect.
CodeFormer Usage#
The following command will perform face restoration with CodeFormer instead of the default gfpgan.
<prompt> -G 0.8 -ft codeformer
Other Options#
-cf- cf or CodeFormer Fidelity takes values between0and1. 0 produces high quality results but low accuracy and 1 produces lower quality results but higher accuacy to your original face.
The following command will perform face restoration with CodeFormer. CodeFormer will output a result that is closely matching to the input face.
<prompt> -G 1.0 -ft codeformer -cf 0.9
The following command will perform face restoration with CodeFormer. CodeFormer will output a result that is the best restoration possible. This may deviate slightly from the original face. This is an excellent option to use in situations when there is very little facial data to work with.
<prompt> -G 1.0 -ft codeformer -cf 0.1
Fixing Previously-Generated Images#
It is easy to apply face restoration and/or upscaling to any
previously-generated file. Just use the syntax
!fix path/to/file.png <options>. For example, to apply GFPGAN at strength 0.8
and upscale 2X for a file named ./outputs/img-samples/000044.2945021133.png,
just run:
A new file named 000044.2945021133.fixed.png will be created in the output
directory. Note that the !fix command does not replace the original file,
unlike the behavior at generate time.
How to disable#
If, for some reason, you do not wish to load the GFPGAN and/or ESRGAN libraries,
you can disable them on the invoke.py command line with the --no_restore and
--no_upscale options, respectively.
Created: September 11, 2022