2022-09-21 06:53:08 +00:00
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---
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title: Outpainting
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---
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# :octicons-paintbrush-16: Outpainting
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refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
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## Outpainting and outcropping
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Outpainting is a process by which the AI generates parts of the image that are
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outside its original frame. It can be used to fix up images in which the subject
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is off center, or when some detail (often the top of someone's head!) is cut
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off.
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2022-11-05 13:36:45 +00:00
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InvokeAI supports two versions of outpainting, one called "outpaint" and the
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other "outcrop." They work slightly differently and each has its advantages and
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drawbacks.
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2022-09-21 06:53:08 +00:00
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2022-10-27 22:42:51 +00:00
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### Outpainting
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Outpainting is the same as inpainting, except that the painting occurs in the
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regions outside of the original image. To outpaint using the `invoke.py` command
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line script, prepare an image in which the borders to be extended are pure
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black. Add an alpha channel (if there isn't one already), and make the borders
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completely transparent and the interior completely opaque. If you wish to modify
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the interior as well, you may create transparent holes in the transparency
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layer, which `img2img` will paint into as usual.
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2022-10-27 22:42:51 +00:00
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2022-11-05 13:36:45 +00:00
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Pass the image as the argument to the `-I` switch as you would for regular
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inpainting:
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2022-11-05 13:36:45 +00:00
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```bash
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invoke> a stream by a river -I /path/to/transparent_img.png
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```
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You'll likely be delighted by the results.
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### Tips
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1. Do not try to expand the image too much at once. Generally it is best to
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expand the margins in 64-pixel increments. 128 pixels often works, but your
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mileage may vary depending on the nature of the image you are trying to
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outpaint into.
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2. There are a series of switches that can be used to adjust how the inpainting
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algorithm operates. In particular, you can use these to minimize the seam
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that sometimes appears between the original image and the extended part.
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These switches are:
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| switch | default | description |
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| -------------------------- | ------- | ---------------------------------------------------------------------- |
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| `--seam_size SEAM_SIZE ` | `0` | Size of the mask around the seam between original and outpainted image |
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| `--seam_blur SEAM_BLUR` | `0` | The amount to blur the seam inwards |
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| `--seam_strength STRENGTH` | `0.7` | The img2img strength to use when filling the seam |
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| `--seam_steps SEAM_STEPS` | `10` | The number of steps to use to fill the seam. |
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| `--tile_size TILE_SIZE` | `32` | The tile size to use for filling outpaint areas |
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2022-10-27 22:42:51 +00:00
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refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
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### Outcrop
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The `outcrop` extension gives you a convenient `!fix` postprocessing command
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that allows you to extend a previously-generated image in 64 pixel increments in
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any direction. You can apply the module to any image previously-generated by
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InvokeAI. Note that it works with arbitrary PNG photographs, but not currently
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with JPG or other formats. Outcropping is particularly effective when combined
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with the
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[runwayML custom inpainting model](INPAINTING.md#using-the-runwayml-inpainting-model).
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2022-09-21 06:53:08 +00:00
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refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
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Consider this image:
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2022-10-17 22:40:54 +00:00
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<figure markdown>
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refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
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![curly_woman](../assets/outpainting/curly.png)
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</figure>
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refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
2022-10-03 20:53:12 +00:00
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2022-11-05 13:36:45 +00:00
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Pretty nice, but it's annoying that the top of her head is cut off. She's also a
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bit off center. Let's fix that!
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2022-10-11 20:10:35 +00:00
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```bash
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invoke> !fix images/curly.png --outcrop top 128 right 64 bottom 64
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```
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This is saying to apply the `outcrop` extension by extending the top of the
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image by 128 pixels, and the right and bottom of the image by 64 pixels. You can
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use any combination of top|left|right|bottom, and specify any number of pixels
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to extend. You can also abbreviate `--outcrop` to `-c`.
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2022-09-21 06:53:08 +00:00
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refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
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The result looks like this:
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<figure markdown>
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![curly_woman_outcrop](../assets/outpainting/curly-outcrop-2.png)
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</figure>
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The new image is larger than the original (576x704) because 64 pixels were added
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to the top and right sides. You will need enough VRAM to process an image of
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this size.
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2022-09-21 06:53:08 +00:00
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refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
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A number of caveats:
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1. Although you can specify any pixel values, they will be rounded up to the
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nearest multiple of 64. Smaller values are better. Larger extensions are more
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likely to generate artefacts. However, if you wish you can run the !fix
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command repeatedly to cautiously expand the image.
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2. The extension is stochastic, meaning that each time you run it you'll get a
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slightly different result. You can run it repeatedly until you get an image
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you like. Unfortunately `!fix` does not currently respect the `-n`
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(`--iterations`) argument.
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3. Your results will be _much_ better if you use the `inpaint-1.5` model
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released by runwayML and installed by default by `scripts/preload_models.py`.
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This model was trained specifically to harmoniously fill in image gaps. The
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standard model will work as well, but you may notice color discontinuities at
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the border.
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4. When using the `inpaint-1.5` model, you may notice subtle changes to the area
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outside the masked region. This is because the model performs an
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encoding/decoding on the image as a whole. This does not occur with the
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standard model.
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2022-11-03 19:44:06 +00:00
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refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
2022-10-03 20:53:12 +00:00
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## Outpaint
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2022-09-21 06:53:08 +00:00
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2022-11-05 13:36:45 +00:00
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The `outpaint` extension does the same thing, but with subtle differences.
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Starting with the same image, here is how we would add an additional 64 pixels
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to the top of the image:
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2022-09-21 06:53:08 +00:00
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2022-10-11 20:10:35 +00:00
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```bash
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2022-10-08 13:32:06 +00:00
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invoke> !fix images/curly.png --out_direction top 64
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2022-10-11 20:10:35 +00:00
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```
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2022-09-21 06:53:08 +00:00
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2022-10-09 22:46:23 +00:00
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(you can abbreviate `--out_direction` as `-D`.
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2022-09-21 06:53:08 +00:00
|
|
|
|
refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
2022-10-03 20:53:12 +00:00
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|
The result is shown here:
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2022-09-21 06:53:08 +00:00
|
|
|
|
2022-10-17 22:40:54 +00:00
|
|
|
<figure markdown>
|
refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
2022-10-03 20:53:12 +00:00
|
|
|
![curly_woman_outpaint](../assets/outpainting/curly-outpaint.png)
|
2022-10-17 22:40:54 +00:00
|
|
|
</figure>
|
2022-09-21 06:53:08 +00:00
|
|
|
|
refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
2022-10-03 20:53:12 +00:00
|
|
|
Although the effect is similar, there are significant differences from
|
|
|
|
outcropping:
|
|
|
|
|
2022-10-11 20:10:35 +00:00
|
|
|
- You can only specify one direction to extend at a time.
|
|
|
|
- The image is **not** resized. Instead, the image is shifted by the specified
|
2022-11-05 13:36:45 +00:00
|
|
|
number of pixels. If you look carefully, you'll see that less of the lady's
|
|
|
|
torso is visible in the image.
|
|
|
|
- Because the image dimensions remain the same, there's no rounding to multiples
|
|
|
|
of 64.
|
|
|
|
- Attempting to outpaint larger areas will frequently give rise to ugly ghosting
|
|
|
|
effects.
|
2022-10-11 20:10:35 +00:00
|
|
|
- For best results, try increasing the step number.
|
2022-11-05 13:36:45 +00:00
|
|
|
- If you don't specify a pixel value in `-D`, it will default to half of the
|
|
|
|
whole image, which is likely not what you want.
|
refactor how postprocessors work
- similar call structures for outpainting, outcropping and face restoration modules
- added documentation for outcropping
- post-processing steps now leave a provenance chain (of sorts) in the sd-metadata field:
~~~
scripts/sd-metadata.py outputs/img-samples/curly.942491079.upscale.png
outputs/img-samples/curly.942491079.upscale.png:
{
"model": "stable diffusion",
"model_id": "stable-diffusion-1.4",
"model_hash": "fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556",
"app_id": "lstein/stable-diffusion",
"app_version": "v1.15",
"image": {
"height": 512,
"width": 512,
"steps": 50,
"cfg_scale": 7.5,
"seed": 942491079,
"prompt": [
{
"prompt": "pretty curly-haired redhead woman",
"weight": 1.0
}
],
"postprocessing": [
{
"tool": "outcrop",
"dream_command": "!fix \"test-pictures/curly.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -c top 64 right 64"
},
{
"tool": "gfpgan",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.outcrop-02.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -G 0.8"
},
{
"tool": "upscale",
"dream_command": "!fix \"outputs/img-samples/curly.942491079.gfpgan.png\" -s 50 -S 942491079 -W 512 -H 512 -C 7.5 -A k_lms -U 4.0 0.75"
}
],
"sampler": "k_lms",
"variations": [],
"type": "txt2img"
}
}
~~~
2022-10-03 20:53:12 +00:00
|
|
|
|
2022-10-11 20:10:35 +00:00
|
|
|
!!! tip
|
2022-09-21 06:53:08 +00:00
|
|
|
|
2022-10-11 20:10:35 +00:00
|
|
|
Neither `outpaint` nor `outcrop` are perfect, but we continue to tune
|
|
|
|
and improve them. If one doesn't work, try the other. You may also
|
|
|
|
wish to experiment with other `img2img` arguments, such as `-C`, `-f`
|
|
|
|
and `-s`.
|