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ValueError when using inpaint with inpaint at full resolution option #46
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After further looking into it, it actually seems like pulling the latest commits from the repo, destroyed the whole img2img page.
Creating a new venv and installing all components via the install instructions yields the same result, so I really hope this error isn't only happening on my end. If further information is needed, I'll gladly provide more. |
i can't seem to reproduce this did you possibly update script and re-lauch the gradio process with updating the web page? |
created a new venv with python 3.10.6, installed from scratch, everything works |
I'm sorry for the confusion. I updated python to 3.10.6 and again followed the instructions in a new venv. |
The inpainting works in Firefox, but does not work in Chrome Version 104.0.5112.102 (64Bit) and 105.0.5195.54 (64Bit). |
Do you have any extensions loaded in Chrome? Those seem to break inpainting (particularly DuckDuckGo privacy essentials). |
Yes, it's gotta be DuckDuckGo. |
still broken (inpaint sketch), even in firefox
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I'm sorry to also bump this... but the issue with values being swapped in the tuple returned by doesn't have anything to do with duckduckgo, or not? pad being 0 and crop_* being w and h?
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Found a solution that worked for me at least, using latest commit & model v1.5. in firefox, Duckduckgo privacy essentials can be whitelisted for 127.0.0.1, (gear symbol in extension is available on 'normal' sites, add unprotected site.) I also whitelisted it in several other privacy extensions. Error is now gone for inpaint. |
…ting add support for prompt weighting
Currently the inpaint for img2img conversion is not working on my end. It seems like the mask is not working as intended / is not applied at all. My current PIL version is
Name: Pillow, Version: 9.2.0
and the current Numpy version isName: numpy Version: 1.23.2
.The 4-tuple crop_reagion leading to this error is
(448, 448, 64, 64)
.Error:
Image to demonstrate the error:
Further, disabling inpaint at full resolution leads to interference and an output, but the output image is exactly the same as the input image, as if the mask was never applied.
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