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title: Upscale title: Upscale
--- ---
# :material-image-size-select-large: Upscale # :material-image-size-select-large: Upscale
## **Intro** ## **Intro**
@ -11,8 +12,6 @@ The script provides the ability to restore faces and upscale.
You can enable these features by passing `--restore` and `--esrgan` to your launch script to enable You can enable these features by passing `--restore` and `--esrgan` to your launch script to enable
face restoration modules and upscaling modules respectively. face restoration modules and upscaling modules respectively.
## **GFPGAN and Real-ESRGAN Support**
The default face restoration module is GFPGAN and the default upscaling module is ESRGAN. The default face restoration module is GFPGAN and the default upscaling module is ESRGAN.
As of version 1.14, environment.yaml will install the Real-ESRGAN package into the standard install As of version 1.14, environment.yaml will install the Real-ESRGAN package into the standard install
@ -46,11 +45,11 @@ other GFPGAN related boot arguments if you wish to customize further._
may run `python3 scripts/preload_models.py` after you have installed GFPGAN and all its may run `python3 scripts/preload_models.py` after you have installed GFPGAN and all its
dependencies. dependencies.
## **Usage** ## Usage
You will now have access to two new prompt arguments. You will now have access to two new prompt arguments.
### **Upscaling** ### Upscaling
`-U : <upscaling_factor> <upscaling_strength>` `-U : <upscaling_factor> <upscaling_strength>`
@ -64,7 +63,7 @@ retain some of those for natural looking results, we recommend using values betw
If you do not explicitly specify an upscaling_strength, it will default to 0.75. If you do not explicitly specify an upscaling_strength, it will default to 0.75.
### **Face Restoration** ### Face Restoration
`-G : <gfpgan_strength>` `-G : <gfpgan_strength>`
@ -81,7 +80,7 @@ When you use either `-U` or `-G`, the final result you get is upscaled or face m
to save the original Stable Diffusion generation, you can use the `-save_orig` prompt argument to to save the original Stable Diffusion generation, you can use the `-save_orig` prompt argument to
save the original unaffected version too. save the original unaffected version too.
### **Example Usage** ### Example Usage
```bash ```bash
dream> superman dancing with a panda bear -U 2 0.6 -G 0.4 dream> superman dancing with a panda bear -U 2 0.6 -G 0.4
@ -121,13 +120,13 @@ saving it to `ldm/restoration/codeformer/weights` folder.
You can use `-ft` prompt argument to swap between CodeFormer and the default GFPGAN. The above 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. mentioned `-G` prompt argument will allow you to control the strength of the restoration effect.
### **Usage:** ### Usage:
The following command will perform face restoration with CodeFormer instead of the default gfpgan. The following command will perform face restoration with CodeFormer instead of the default gfpgan.
`<prompt> -G 0.8 -ft codeformer` `<prompt> -G 0.8 -ft codeformer`
**Other Options:** ### Other Options:
- `-cf` - cf or CodeFormer Fidelity takes values between `0` and `1`. 0 produces high quality - `-cf` - cf or CodeFormer Fidelity takes values between `0` and `1`. 0 produces high quality
results but low accuracy and 1 produces lower quality results but higher accuacy to your original results but low accuracy and 1 produces lower quality results but higher accuacy to your original
@ -143,3 +142,25 @@ that is the best restoration possible. This may deviate slightly from the origin
excellent option to use in situations when there is very little facial data to work with. 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` `<prompt> -G 1.0 -ft codeformer -cf 0.1`
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## 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:
~~~~
dream> !fix ./outputs/img-samples/000044.2945021133.png -G 0.8 -U 2
~~~~
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.
### Disabling:
If, for some reason, you do not wish to load the GFPGAN and/or ESRGAN libraries, you can disable them
on the dream.py command line with the `--no_restore` and `--no_upscale` options, respectively.
>>>>>>> Update UPSCALE.md