alisson-anjos
a2b499ce3e
Two compounding mistakes in 1.37.0's derivation, reported as a hole much larger than the head with the new head generated floating inside it: - the upward slack was scaled by the mask's HEIGHT (hh * delta / tilt). Height swings with how much neck the mask took, and a portrait-shaped identity image (tilt < 1) multiplied it further: a 300x400 head with a 0.6 reference asked for 136 px above. Every slack is now a fraction of the head's WIDTH, the stable dimension, capped at 25% sideways and 30% up. - latent_mask_dilate was derived from mask_grow and forced to at least one cell, which added a whole 32 px on EVERY side -- including down, which the pixel grow deliberately holds at the base -- on top of a grow that already carried the slack. It is 0 now: _mask_to_latent reduces with MAX, so any cell the mask touches is fully editable already. The same head asked for 4 cells, 128 px, before this. Also undo the guider injections in reverse: with several chunks each injection captured the state the previous one left, so undoing forwards restored chunk 1's specs onto the guider instead of clearing them. Tests pin both: growth stays under 45% of the head's width across every reference aspect and headroom, the latent dilation stays 0, and the crop box always holds the grow plus the feather.
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).
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 (-8pixel 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.