alisson-anjosandClaude Opus 5
f03f012fce
Builds a ShotPlan-format multishot prompt (global preamble + "Shot N: <modifier> <size> <move> <action>" blocks) plus the ordered, gray-padded reference batch that the multishot strata LoRA expects. No new conditioning node is needed: LTX Identity Transfer already assigns seg_value = (source_id + i) * phase_scale and strata_slot = i over the image batch, so source_id=2 with layout="strata" over 4 refs reproduces the trained convention (source_id 2/3/4/5 on slots 0/1/2/3). Batch order is shot order -- the LoRA was trained with shuffle_reference_slots=false. Unused slots get a flat RGB-128 frame, matching the dataset's blank.jpg placeholder. The dropdown vocabularies are extracted from the 12,470 "Shot N:" headers of Pensioner/shotplan train_meta_16fps.json (the span between "Shot N:" and the start of the action sentence), covering 98% of size terms and 97% of move terms. Modifiers (over-the-shoulder, low/high angle, POV) are a separate axis that combines with a size rather than replacing it, as in the source captions. Bump version to 1.21.1. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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_framesoptional: 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.
Recommended Starting Values
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).
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.