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https://github.com/invoke-ai/InvokeAI
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99 lines
3.4 KiB
Markdown
99 lines
3.4 KiB
Markdown
# **GFPGAN and Real-ESRGAN Support**
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The script also provides the ability to do face restoration and
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upscaling with the help of GFPGAN and Real-ESRGAN respectively.
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To use the ability, clone the **[GFPGAN
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repository](https://github.com/TencentARC/GFPGAN)** and follow their
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installation instructions. By default, we expect GFPGAN to be
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installed in a 'GFPGAN' sibling directory. Be sure that the `"ldm"`
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conda environment is active as you install GFPGAN.
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You can use the `--gfpgan_dir` argument with `dream.py` to set a
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custom path to your GFPGAN directory. _There are other GFPGAN related
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boot arguments if you wish to customize further._
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You can install **Real-ESRGAN** by typing the following command.
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```
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pip install realesrgan
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```
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**Note: Internet connection needed:**
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Users whose GPU machines are isolated from the Internet (e.g. on a
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University cluster) should be aware that the first time you run
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dream.py with GFPGAN and Real-ESRGAN turned on, it will try to
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download model files from the Internet. To rectify this, you may run
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`python3 scripts/preload_models.py` after you have installed GFPGAN
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and all its dependencies.
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**Usage**
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You will now have access to two new prompt arguments.
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**Upscaling**
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`-U : <upscaling_factor> <upscaling_strength>`
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The upscaling prompt argument takes two values. The first value is a
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scaling factor and should be set to either `2` or `4` only. This will
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either scale the image 2x or 4x respectively using different models.
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You can set the scaling stength between `0` and `1.0` to control
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intensity of the of the scaling. This is handy because AI upscalers
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generally tend to smooth out texture details. If you wish to retain
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some of those for natural looking results, we recommend using values
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between `0.5 to 0.8`.
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If you do not explicitly specify an upscaling_strength, it will
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default to 0.75.
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**Face Restoration**
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`-G : <gfpgan_strength>`
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This prompt argument controls the strength of the face restoration
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that is being applied. Similar to upscaling, values between `0.5 to 0.8` are recommended.
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You can use either one or both without any conflicts. In cases where
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you use both, the image will be first upscaled and then the face
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restoration process will be executed to ensure you get the highest
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quality facial features.
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`--save_orig`
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When you use either `-U` or `-G`, the final result you get is upscaled
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or face modified. If you want to save the original Stable Diffusion
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generation, you can use the `-save_orig` prompt argument to save the
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original unaffected version too.
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**Example Usage**
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```
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dream > superman dancing with a panda bear -U 2 0.6 -G 0.4
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```
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This also works with img2img:
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```
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dream> a man wearing a pineapple hat -I path/to/your/file.png -U 2 0.5 -G 0.6
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```
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**Note**
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GFPGAN and Real-ESRGAN are both memory intensive. In order to avoid
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crashes and memory overloads during the Stable Diffusion process,
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these effects are applied after Stable Diffusion has completed its
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work.
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In single image generations, you will see the output right away but
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when you are using multiple iterations, the images will first be
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generated and then upscaled and face restored after that process is
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complete. While the image generation is taking place, you will still
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be able to preview the base images.
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If you wish to stop during the image generation but want to upscale or
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face restore a particular generated image, pass it again with the same
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prompt and generated seed along with the `-U` and `-G` prompt
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arguments to perform those actions.
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