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update IMG2IMG.md
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@ -12,21 +12,19 @@ stable diffusion to build the prompt on top of the image you provide, preserving
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the original's basic shape and layout. To use it, provide the `--init_img`
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option as shown here:
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```commandline
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tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
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```
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!!! example ""
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This will take the original image shown here:
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```commandline
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tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
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```
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<figure markdown>
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{ width=320 }
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</figure>
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<figure markdown>
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and generate a new image based on it as shown here:
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| original image | generated image |
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| :------------: | :-------------: |
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| { width=320 } | { width=320 } |
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<figure markdown>
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{ width=320 }
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</figure>
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</figure>
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The `--init_img` (`-I`) option gives the path to the seed picture. `--strength`
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(`-f`) controls how much the original will be modified, ranging from `0.0` (keep
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@ -88,13 +86,15 @@ from a prompt. If the step count is 10, then the "latent space" (Stable
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Diffusion's internal representation of the image) for the prompt "fire" with
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seed `1592514025` develops something like this:
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```bash
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invoke> "fire" -s10 -W384 -H384 -S1592514025
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```
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!!! example ""
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<figure markdown>
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</figure>
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```bash
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invoke> "fire" -s10 -W384 -H384 -S1592514025
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```
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<figure markdown>
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{ width=720 }
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</figure>
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Put simply: starting from a frame of fuzz/static, SD finds details in each frame
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that it thinks look like "fire" and brings them a little bit more into focus,
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@ -109,25 +109,23 @@ into the sequence at the appropriate point, with just the right amount of noise.
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### A concrete example
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I want SD to draw a fire based on this hand-drawn image:
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!!! example "I want SD to draw a fire based on this hand-drawn image"
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<figure markdown>
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</figure>
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{ align=left }
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Let's only do 10 steps, to make it easier to see what's happening. If strength
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is `0.7`, this is what the internal steps the algorithm has to take will look
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like:
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Let's only do 10 steps, to make it easier to see what's happening. If strength
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is `0.7`, this is what the internal steps the algorithm has to take will look
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like:
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<figure markdown>
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</figure>
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<figure markdown>
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</figure>
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With strength `0.4`, the steps look more like this:
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With strength `0.4`, the steps look more like this:
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<figure markdown>
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</figure>
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<figure markdown>
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</figure>
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Notice how much more fuzzy the starting image is for strength `0.7` compared to
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`0.4`, and notice also how much longer the sequence is with `0.7`:
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