Ip adapter attention mask. IP-adapter (Image Prompt adapter) is a Stable Diffusion add-on for using images as prompts, similar to Midjourney and DaLLE 3. preprocess() to generate This workflow mostly showcases the new IPAdapter attention masking feature. prepare_attention_mask(attention_mask, sequence_length, batch_size) # scaled_dot_product_attention expects attention_mask shape to be # (batch, heads, source_length, target_length). The generation happens in just one pass with one KSampler (no inpainting or area conditioning). 2024/07/11: Added experimental Precise composition (layout) transfer. The new IPAdapterClipVisionEnhancer tries to catch small details by tiling the embeds (instead of the image in the pixel space), the result is a slightly higher resolution visual embedding with no cost of performance. For each input IP-Adapter image, you must provide a binary mask. This I did an update yesterday and noticed the mask input appeared on the Apply IPAdapter node. IPAdapterMaskProcessor. Exciting new feature for the IPAdapter extesion: it's now possible to mask part of the composition to affect only a certain area And you can use multiple masks for a perfect result. prepare_attention_mask(attention_mask, sequence_length, batch_size) # scaled_dot_product_attention expects attention_mask shape to be # (batch, heads, source_length, target_length) Exciting new feature for the IPAdapter extesion: it's now possible to mask part of the composition to affect only a certain area And you can use multiple masks for a perfect result. It's exactly the thing I was needing. Once I figured out what it did I was in love. This is useful for composing more than one IP-Adapter image. You can use it to copy the style, composition, or a face in the reference image. Binary masks specify which portion of the output image should be assigned to an IP-Adapter. To start, preprocess the input IP-Adapter images with the ~image_processor. In this example I'm using 2 main characters and a background in completely different styles. attention_mask = attn. fokycdcefzvmhnzsxnajantksefvpwjwaxlhpxeylcgerjhfdzkbrq