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This code (suggested by @abvgdeabvgde2 ) literally does the same thing and it does not break with Python 3.9, making it helpful for Google Colab users (me included).
fixes #8927
Also a partial fix for #8902 but it does not resolve the unresponsive UI problem faced by @Archon332
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The loopback script did not set masked content to original after first loop. So each loop would apply a fill, or latent mask. This would essentially reset progress each loop.
The desired behavior is to use the mask for the first loop, then continue to iterate on the results of the previous loop.
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- Improved user experience. You can now pick the denoising strength of the final loop and one of three curves. Previously you picked a multiplier such as 0.98 or 1.03 to define the change to the denoising strength for each loop. You had to do a ton of math in your head to visualize what was happening. The new UX makes it very easy to understand what's going on and tweak.
- For batch sizes over 1, intermediate images no longer returned. For a batch size of 1, intermediate images from each loop will continue to be returned. When more than 1 image is returned, a grid will also be generated. Previously for larger jobs, you'd get back a mess of many grids and potentially hundreds of images with no organization. To make large jobs usable, only final images are returned.
- Added support for skipping current image. Fixed interrupt to cleanly end and return images. Previously these would throw.
- Improved tooltip descriptions
- Fix some edge cases
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in ids for scripts that only exist on one tab
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prefixes from img exclusive scripts
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Before a new batch would use the last image from the previous batch. Now
each batch will use the original image for the init image at the start of the
batch.
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image and use that instead of extracting from previous image in a loop #481 #541
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honor save grids and how grids in web setting
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