Claude 8ba0ea9620 Add nested-safe H3 latent saver (1.27.0)
The stock SaveLatent calls .contiguous() straight on samples["samples"], which
fails on H3 because the latent is a NestedTensor holding the video and audio
components. This unbinds them first and writes each as its own tensor, so an H3
latent can be taken out of the graph and decoded or inspected offline.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-21 02:04:42 +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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