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@ -4,35 +4,13 @@ title: Postprocessing
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# :material-image-edit: Postprocessing
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# :material-image-edit: Postprocessing
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## Intro
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This sections details the ability to improve faces and upscale images.
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This extension provides the ability to restore faces and upscale images.
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## Face Fixing
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## Face Fixing
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The default face restoration module is GFPGAN. The default upscale is
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As of InvokeAI 3.0, the easiest way to improve faces created during image generation is through the Inpainting functionality of the Unified Canvas. Simply add the image containing the faces that you would like to improve to the canvas, mask the face to be improved and run the invocation. For best results, make sure to use an inpainting specific model; these are usually identified by the "-inpainting" term in the model name.
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Real-ESRGAN. For an alternative face restoration module, see
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[CodeFormer Support](#codeformer-support) below.
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As of version 1.14, environment.yaml will install the Real-ESRGAN package into
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## Upscaling
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the standard install location for python packages, and will put GFPGAN into a
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subdirectory of "src" in the InvokeAI directory. Upscaling with Real-ESRGAN
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should "just work" without further intervention. Simply indicate the desired scale on
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the popup in the Web GUI.
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**GFPGAN** requires a series of downloadable model files to work. These are
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loaded when you run `invokeai-configure`. If GFPAN is failing with an
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error, please run the following from the InvokeAI directory:
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```bash
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invokeai-configure
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```
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If you do not run this script in advance, the GFPGAN module will attempt to
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download the models files the first time you try to perform facial
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reconstruction.
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### Upscaling
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Open the upscaling dialog by clicking on the "expand" icon located
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Open the upscaling dialog by clicking on the "expand" icon located
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above the image display area in the Web UI:
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above the image display area in the Web UI:
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@ -41,82 +19,23 @@ above the image display area in the Web UI:
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![upscale1](../assets/features/upscale-dialog.png)
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![upscale1](../assets/features/upscale-dialog.png)
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</figure>
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</figure>
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There are three different upscaling parameters that you can
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The default upscaling option is Real-ESRGAN x2 Plus, which will scale your image by a factor of two. This means upscaling a 512x512 image will result in a new 1024x1024 image.
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adjust. The first is the scale itself, either 2x or 4x.
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The second is the "Denoising Strength." Higher values will smooth out
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Other options are the x4 upscalers, which will scale your image by a factor of 4.
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the image and remove digital chatter, but may lose fine detail at
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higher values.
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Third, "Upscale Strength" allows you to adjust how the You can set the
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scaling stength between `0` and `1.0` to control the intensity of the
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scaling. AI upscalers generally tend to smooth out texture details. If
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you wish to retain some of those for natural looking results, we
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recommend using values between `0.5 to 0.8`.
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[This figure](../assets/features/upscaling-montage.png) illustrates
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the effects of denoising and strength. The original image was 512x512,
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4x scaled to 2048x2048. The "original" version on the upper left was
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scaled using simple pixel averaging. The remainder use the ESRGAN
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upscaling algorithm at different levels of denoising and strength.
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<figure markdown>
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![upscaling](../assets/features/upscaling-montage.png){ width=720 }
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</figure>
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Both denoising and strength default to 0.75.
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### Face Restoration
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InvokeAI offers alternative two face restoration algorithms,
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[GFPGAN](https://github.com/TencentARC/GFPGAN) and
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[CodeFormer](https://huggingface.co/spaces/sczhou/CodeFormer). These
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algorithms improve the appearance of faces, particularly eyes and
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mouths. Issues with faces are less common with the latest set of
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Stable Diffusion models than with the original 1.4 release, but the
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restoration algorithms can still make a noticeable improvement in
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certain cases. You can also apply restoration to old photographs you
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upload.
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To access face restoration, click the "smiley face" icon in the
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toolbar above the InvokeAI image panel. You will be presented with a
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dialog that offers a choice between the two algorithm and sliders that
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allow you to adjust their parameters. Alternatively, you may open the
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left-hand accordion panel labeled "Face Restoration" and have the
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restoration algorithm of your choice applied to generated images
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automatically.
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Like upscaling, there are a number of parameters that adjust the face
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restoration output. GFPGAN has a single parameter, `strength`, which
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controls how much the algorithm is allowed to adjust the
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image. CodeFormer has two parameters, `strength`, and `fidelity`,
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which together control the quality of the output image as described in
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the [CodeFormer project
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page](https://shangchenzhou.com/projects/CodeFormer/). Default values
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are 0.75 for both parameters, which achieves a reasonable balance
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between changing the image too much and not enough.
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[This figure](../assets/features/restoration-montage.png) illustrates
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the effects of adjusting GFPGAN and CodeFormer parameters.
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<figure markdown>
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![upscaling](../assets/features/restoration-montage.png){ width=720 }
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</figure>
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!!! note
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!!! note
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GFPGAN and Real-ESRGAN are both memory intensive. In order to avoid crashes and memory overloads
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Real-ESRGAN is memory intensive. In order to avoid crashes and memory overloads
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during the Stable Diffusion process, these effects are applied after Stable Diffusion has completed
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during the Stable Diffusion process, these effects are applied after Stable Diffusion has completed
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its work.
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its work.
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In single image generations, you will see the output right away but when you are using multiple
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In single image generations, you will see the output right away but when you are using multiple
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iterations, the images will first be generated and then upscaled and face restored after that
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iterations, the images will first be generated and then upscaled after that
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process is complete. While the image generation is taking place, you will still be able to preview
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process is complete. While the image generation is taking place, you will still be able to preview
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the base images.
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the base images.
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## How to disable
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## How to disable
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If, for some reason, you do not wish to load the GFPGAN and/or ESRGAN libraries,
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If, for some reason, you do not wish to load the ESRGAN libraries,
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you can disable them on the invoke.py command line with the `--no_restore` and
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you can disable them on the invoke.py command line with the `--no_esrgan` options.
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`--no_esrgan` options, respectively.
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