Multi-image masking for single IP Adapter#7499
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sayakpaul
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Changes looking nice ❤️ Great work as always. Let's add a fast test and see how it goes?
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
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thank you @sayakpaul ready |
| max_diff = numpy_cosine_similarity_distance(image_slice, expected_slice) | ||
| assert max_diff < 5e-4 | ||
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| def test_ip_adapter_multiple_masks_one_adapter(self): |
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This is slow test. I was wondering if it's possible to add a fast test like
?
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I see, I missed that
I'll add it now
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
yiyixuxu
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thank you for working on this!
looks good. I left some feedbacks. let's make very clear what's the expected shape for ip_adapter_mask and scale
Co-authored-by: YiYi Xu <yixu310@gmail.com>
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@yiyixuxu @sayakpaul now it's ready |
yiyixuxu
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looks good to me!
I will run slow tests to make sure it does not break anything before merge
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thank you YiYi! I fixed the fast test for the panorama pipeline that was failing and the slow test I ran all the slow tests related to image masking locally and they didn't break :) |
* Support multiimage masking --------- Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: YiYi Xu <yixu310@gmail.com>
What does this PR do?
Image masking is currently supported by passing a mask and an image for each IP Adapter in the pipeline.
This PR extends this usage by allowing multiple masks and images to be passed to a single IP Adapter. Scales must be passed accordingly.
Discussed in #7419
@sayakpaul @yiyixuxu