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https://github.com/invoke-ai/InvokeAI
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199 lines
8.1 KiB
Markdown
199 lines
8.1 KiB
Markdown
---
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title: Inpainting
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---
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# :octicons-paintbrush-16: Inpainting
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## **Creating Transparent Regions for Inpainting**
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Inpainting is really cool. To do it, you start with an initial image
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and use a photoeditor to make one or more regions transparent
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(i.e. they have a "hole" in them). You then provide the path to this
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image at the dream> command line using the `-I` switch. Stable
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Diffusion will only paint within the transparent region.
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There's a catch. In the current implementation, you have to prepare
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the initial image correctly so that the underlying colors are
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preserved under the transparent area. Many imaging editing
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applications will by default erase the color information under the
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transparent pixels and replace them with white or black, which will
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lead to suboptimal inpainting. It often helps to apply incomplete
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transparency, such as any value between 1 and 99%
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You also must take care to export the PNG file in such a way that the
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color information is preserved. There is often an option in the export
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dialog that lets you specify this.
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If your photoeditor is erasing the underlying color information,
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`dream.py` will give you a big fat warning. If you can't find a way to
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coax your photoeditor to retain color values under transparent areas,
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then you can combine the `-I` and `-M` switches to provide both the
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original unedited image and the masked (partially transparent) image:
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```bash
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invoke> "man with cat on shoulder" -I./images/man.png -M./images/man-transparent.png
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```
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## **Masking using Text**
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You can also create a mask using a text prompt to select the part of
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the image you want to alter, using the <a
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href="https://github.com/timojl/clipseg">clipseg</a> algorithm. This
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works on any image, not just ones generated by InvokeAI.
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The `--text_mask` (short form `-tm`) option takes two arguments. The
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first argument is a text description of the part of the image you wish
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to mask (paint over). If the text description contains a space, you must
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surround it with quotation marks. The optional second argument is the
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minimum threshold for the mask classifier's confidence score, described
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in more detail below.
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To see how this works in practice, here's an image of a still life
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painting that I got off the web.
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<img src="../assets/still-life-scaled.jpg">
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You can selectively mask out the
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orange and replace it with a baseball in this way:
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~~~
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invoke> a baseball -I /path/to/still_life.png -tm orange
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~~~
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<img src="../assets/still-life-inpainted.png">
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The clipseg classifier produces a confidence score for each region it
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identifies. Generally regions that score above 0.5 are reliable, but
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if you are getting too much or too little masking you can adjust the
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threshold down (to get more mask), or up (to get less). In this
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example, by passing `-tm` a higher value, we are insisting on a tigher
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mask. However, if you make it too high, the orange may not be picked
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up at all!
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~~~
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invoke> a baseball -I /path/to/breakfast.png -tm orange 0.6
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~~~
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The `!mask` command may be useful for debugging problems with the
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text2mask feature. The syntax is `!mask /path/to/image.png -tm <text>
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<threshold>`
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It will generate three files:
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- The image with the selected area highlighted.
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- The image with the un-selected area highlighted.
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- The image with the selected area converted into a black and white
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image according to the threshold level.
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Note that none of these images are intended to be used as the mask
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passed to invoke via `-M` and may give unexpected results if you try
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to use them this way. Instead, use `!mask` for testing that you are
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selecting the right mask area, and then do inpainting using the
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best selection term and threshold.
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Here is an example of how `!mask` works:
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```
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invoke> !mask ./test-pictures/curly.png -tm hair 0.5
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>> generating masks from ./test-pictures/curly.png
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>> Initializing clipseg model for text to mask inference
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Outputs:
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[941.1] outputs/img-samples/000019.curly.hair.deselected.png: !mask ./test-pictures/curly.png -tm hair 0.5
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[941.2] outputs/img-samples/000019.curly.hair.selected.png: !mask ./test-pictures/curly.png -tm hair 0.5
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[941.3] outputs/img-samples/000019.curly.hair.masked.png: !mask ./test-pictures/curly.png -tm hair 0.5
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```
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**Original image "curly.png"**
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<img src="../assets/outpainting/curly.png">
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**000019.curly.hair.selected.png**
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<img src="../assets/inpainting/000019.curly.hair.selected.png">
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**000019.curly.hair.deselected.png**
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<img src="../assets/inpainting/000019.curly.hair.deselected.png">
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**000019.curly.hair.masked.png**
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<img src="../assets/inpainting/000019.curly.hair.masked.png">
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It looks like we selected the hair pretty well at the 0.5 threshold
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(which is the default, so we didn't actually have to specify it), so
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let's have some fun:
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```
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invoke> medusa with cobras -I ./test-pictures/curly.png -tm hair 0.5 -C20
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>> loaded input image of size 512x512 from ./test-pictures/curly.png
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...
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Outputs:
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[946] outputs/img-samples/000024.801380492.png: "medusa with cobras" -s 50 -S 801380492 -W 512 -H 512 -C 20.0 -I ./test-pictures/curly.png -A k_lms -f 0.75
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```
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<img src="../assets/inpainting/000024.801380492.png">
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### Inpainting is not changing the masked region enough!
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One of the things to understand about how inpainting works is that it
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is equivalent to running img2img on just the masked (transparent)
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area. img2img builds on top of the existing image data, and therefore
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will attempt to preserve colors, shapes and textures to the best of
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its ability. Unfortunately this means that if you want to make a
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dramatic change in the inpainted region, for example replacing a red
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wall with a blue one, the algorithm will fight you.
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You have a couple of options. The first is to increase the values of
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the requested steps (`-sXXX`), strength (`-f0.XX`), and/or
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condition-free guidance (`-CXX.X`). If this is not working for you, a
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more extreme step is to provide the `--inpaint_replace 0.X` (`-r0.X`)
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option. This value ranges from 0.0 to 1.0. The higher it is the less
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attention the algorithm will pay to the data underneath the masked
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region. At high values this will enable you to replace colored regions
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entirely, but beware that the masked region mayl not blend in with the
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surrounding unmasked regions as well.
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---
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## Recipe for GIMP
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[GIMP](https://www.gimp.org/) is a popular Linux photoediting tool.
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1. Open image in GIMP.
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2. Layer->Transparency->Add Alpha Channel
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3. Use lasso tool to select region to mask
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4. Choose Select -> Float to create a floating selection
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5. Open the Layers toolbar (^L) and select "Floating Selection"
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6. Set opacity to a value between 0% and 99%
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7. Export as PNG
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8. In the export dialogue, Make sure the "Save colour values from
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transparent pixels" checkbox is selected.
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---
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## Recipe for Adobe Photoshop
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1. Open image in Photoshop
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<div align="center" markdown></div>
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2. Use any of the selection tools (Marquee, Lasso, or Wand) to select the area you desire to inpaint.
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<div align="center" markdown></div>
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3. Because we'll be applying a mask over the area we want to preserve, you should now select the inverse by using the ++shift+ctrl+i++ shortcut, or right clicking and using the "Select Inverse" option.
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4. You'll now create a mask by selecting the image layer, and Masking the selection. Make sure that you don't delete any of the underlying image, or your inpainting results will be dramatically impacted.
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<div align="center" markdown></div>
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5. Make sure to hide any background layers that are present. You should see the mask applied to your image layer, and the image on your canvas should display the checkered background.
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<div align="center" markdown></div>
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6. Save the image as a transparent PNG by using `File`-->`Save a Copy` from the menu bar, or by using the keyboard shortcut ++alt+ctrl+s++
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<div align="center" markdown></div>
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7. After following the inpainting instructions above (either through the CLI or the Web UI), marvel at your newfound ability to selectively invoke. Lookin' good!
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<div align="center" markdown></div>
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8. In the export dialogue, Make sure the "Save colour values from transparent pixels" checkbox is selected.
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