I updated Identity Feature Transfer to remove the need for stacked/chained nodes.

clearer screenshot of the wf since reddit compresses the photos

Now the workflow is simpler:

• Use Multi ReferenceLatent for multiple reference images.

• Use Identity Feature Transfer Final for the identity pull.

• If you use masks, connect each mask directly to the matching mask input on the node.

  • subject_mask_1 = mask for reference 1

  • subject_mask_2 = mask for reference 2

  • etc.

The node handles the multi-reference setup internally, so you no longer need multiple stacked identity nodes for each reference.

Presets are still available, similar to the previous version.

For custom tuning, the two main knobs are:

• Temperature

• Similarity

Temperature is the main identity-strength control. Lower temperature gives a stronger, more direct 1:1 identity pull.

Similarity works more like a refiner/filter. It controls how selective the match needs to be before the node pulls from the reference.

So in practice:

• Lower temperature = stronger identity / more faithful match

• Higher temperature = softer, looser identity influence

• Lower similarity = allows more reference matches

• Higher similarity = stricter matching, more selective pull

example workflow (update to version 3.4.1 as there was a conflict with a node from a different repo causing the multireference latent node to be replaced if you had the other custom node installed and now that has been fixed)

Also just a little side note, this Final version uses a bit diff technique in term of pulls so 1:1 is achievable but needs to be careful enough to get it.

Previous posts for context:
multi ref latent

Iden transfer v3