alisson-anjosandClaude Opus 5 1fc84f4f37 Fix the sidecar layout for LTX-2.5 coordinates (1.29.1)
Two wrong assumptions in 1.29.0, both hit by the first real run:

  shape  -- LTX-2.5 hands out patch bounds, [B, 3, N, 2], not the one-corner-per-token
            [B, 3, N] the node was written against. The other layouts survived it by
            accident (their math is elementwise), but each was reducing over tokens only,
            so a patch's start and end bound were shifted by their own separate minima --
            which squeezes the span instead of translating it.
  batch  -- layouts run BEFORE the reference tokens are expanded to the CFG batch, so the
            target arrives [2, ...] while the reference is still [1, ...]. overlap/st_drc
            broadcast out of it; sidecar assigns in place and raised
            "The expanded size of the tensor (1) must match the existing size (2)".

_tass_axis_stats now reduces over every dimension except the T/H/W one -- tokens, the
bounds axis when present, and the batch -- which fixes both at once and keeps the older
[B, 3, N] shape working. Verified against ltx_core.conditioning.reference_layout: all four
layouts now agree with the trainer bit-for-bit on the 2.5 shape, in the exact batch-1
reference vs batch-2 target configuration that crashed.

Also passes the spec's sidecar_margin_pixels through instead of always using the default.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HGYHCVjHe6acihEpCRyn1K
2026-08-23 16:46:38 +00:00
2026-03-17 08:43:45 +00:00
2026-03-19 08:20:51 +00:00
2026-03-19 08:20:51 +00:00
2026-03-19 08:20:51 +00:00

ComfyUI-BFSNodes

This repository includes general video composition helpers and the LTXV Edit Anything nodes required by Edit Anything LoRAs trained for LTX-Video 2.3 style video_to_video_ref_adaln workflows. The first public reference LoRA is expected to be edit_anything_reference_v0.1_r128_12000.safetensors.

Nodes

LTXV Edit Anything (Apply)

A unified conditioning node for LTXV Edit Anything LoRAs. It combines three conditioning paths from one LoRA checkpoint:

  • IC-LoRA sequence conditioning: appends a reference image and optional guide video frames as clean conditioning frames.
  • Role embedding: injects the learned reference-role token embedding before patchify_proj, when the LoRA contains role embedding weights.
  • AdaLN reference conditioning: pools the encoded reference image and injects a global appearance/style condition into the LTXV timestep path, when the LoRA contains the AdaLN projector weights.

Use this node when a LoRA was trained with the Edit Anything / video_to_video_ref_adaln strategy and requires reference-image conditioning beyond a standard LoRA load.

LTXV Apply Neutral Mask

Replaces masked-out regions in an image or video batch with a clean solid background (white, neutral_gray, or black). This is useful for preparing reference images or guide frames before passing them to Edit Anything conditioning.

LTXV Resize Reference By Mask

Resizes a reference object onto a clean canvas using a mask bounding box as the target object size. This helps match the scale expected by the guide/video workflow while keeping the reference image clean.

Video Composition Nodes

The repository also includes the existing BFS video composition utilities:

  • Reserved Region Frame Composer
  • Frame Ranged Face Loader
  • Face Sequence Batch

Installation

Clone this repository into your ComfyUI custom_nodes directory:

cd ComfyUI/custom_nodes
git clone https://github.com/alisson-anjos/ComfyUI-BFSNodes.git

Install the Python dependencies if your ComfyUI environment does not already provide them:

cd ComfyUI-BFSNodes
pip install -r requirements.txt

Restart ComfyUI after installation.

LoRA Placement

Put your Edit Anything LoRA checkpoint in ComfyUI's LoRA folder, for example:

ComfyUI/models/loras/

Subfolders are supported by ComfyUI, so organized paths such as this are fine:

ComfyUI/models/loras/ltx-2/2.3/edit_anything/edit_anything_reference_v0.1_r128_12000.safetensors

Basic Workflow

The expected graph order is:

LTXV model loader
  -> standard ComfyUI Load LoRA
  -> LTXV Edit Anything (Apply)
  -> KSampler / sampler node

Connect the node inputs as follows:

  • model: the model output after the standard LoRA loader.
  • positive / negative: your conditioning.
  • vae: the LTXV VAE.
  • latent: the target video latent.
  • ref_image: the appearance/reference image.
  • lora_name: the same Edit Anything LoRA checkpoint.
  • guide_frames optional: frames used for motion or structure guidance.

The node returns the patched model, updated positive/negative conditioning, updated latent, and a preview of the resized reference image.

Start with:

guide_strength: 1.0
ref_strength: 1.0
role_strength: 1.0
adaln_scale: 1.0
enable_adaln: true
enable_role_embedding: true
resize_mode: pad_to_fit

If the model ignores the reference image, try increasing role_strength. If the output copies color/texture too strongly, reduce adaln_scale.

Compatibility Notes

These nodes target ComfyUI's LTXV/LTX-Video model implementation. The main apply node monkey-patches LTXV internals at runtime so the reference-role embedding and AdaLN conditioning match the training-time conditioning path.

A plain LoRA loader alone is not enough for Edit Anything LoRAs that include role embedding and/or AdaLN reference conditioning. Use the standard LoRA loader first, then pass the result through LTXV Edit Anything (Apply).

Reference temporal offset

Nodes that inject clean appearance references expose a reference-only temporal offset in VAE latent steps. The default is 0, matching the standard frame-zero placement used by existing LoRAs and preserving their expected behavior. Negative values are an experimental way to reduce the overlap frame-0 artifact where the reference composition briefly appears at the start of the generated video.

  • 0: standard frame-zero placement (default)
  • -1: one latent step before frame zero (-8 pixel frames with the standard LTX VAE)
  • -2: two latent steps before frame zero (stronger separation, possibly weaker identity)

The offset is applied only to appearance/reference inputs. Guide videos, masks, identity masks, and target video positions remain unchanged. In LTX Multiple Controls, the field is named identity_temporal_offset_latents and affects only identity_image.

Requirements

  • ComfyUI
  • PyTorch
  • safetensors
  • An LTXV/LTX-Video model and compatible VAE
  • An Edit Anything LoRA trained for this conditioning strategy

License

This project follows the repository license. See LICENSE.

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