ComfyUI-BFSNodes
ComfyUI Custom Nodes including FrameRangedFaceLoader for consistent face editing and framing
Nodes (55)
Turn keyframes (and beats) into an LTXV guide sequence
Turn anime footage photoreal, no reference needed
BFSCropSize tells you the crop size before you build the latent
The fixed reference layout a specific multi-ref LoRA expects
Swap the actor in a clip without training a LoRA
The duet panel, without the sampler
Pin a reference beside the latent, keep your own sampler
Taking the panel back off, the cheap way
Put a new head on an existing video
A sanity-check tap for your model before you burn a render on it
Swap a head in LTX video without the LoRA ever seeing a mask
BFS Head Swap Paste Back — bringing a refined crop home
Find Which Layers Broke Your LoRA, Without Retraining
Turn a Recipe Into a Real .safetensors
Feeding an upscale LoRA the geometry it was trained on
The exact canvas, before anything else happens
A face channel the text encoder never sees
Up to five references, one composite, three fit strategies
Your clip's room with the person scrubbed off it
The shot loop's H3 wiring, done for you
The one H3 node you actually wire per shot
One shot, rendered with the clip pinned beside it
Put the shots back together and keep the soundtrack
Shaping the noise H3 starts from (gently, please)
Stop expecting a video model to follow 30 seconds of guide
Change one piece of a shot without losing the plan
One seed widget, a different roll for every shot
Crack a shot open and use it with any video model
Where are your sampling steps actually going?
Two videos, one player, and a diff map that catches the frame you'd have missed
The one-line fix for VLM-written Edit Anything prompts (it never touches an image)
Merge two FACE_SEQUENCE objects into one
Slice a frame range into a FACE_SEQUENCE
Your mask is white. The LoRA was trained on colored ones.
Text-encode a reference image straight into conditioning
Frontal face plus body, side and back references
The reference-token model patch for LTXV
Copy any subject into an LTX-Video generation
Four reference slots, one node call — because chaining them silently breaks
How Multi Reference Slots keeps them from merging
Multishot LTX prompts have a strict format — stop hand-writing them
The unglamorous collector node that keeps your LTX references in order
Tell the model which tag is which image
Scrub a region down to flat white, gray, or black before conditioning
The full Edit Anything conditioning stack, chunked for long clips
Load the sidecar file instead of the LoRA
Put a number on 'did this actually change anything'
Compare two latents before you spend a VAE decode on either
Scale a reference object to match a target's mask, not just its frame
Your H3 output looks like a checkerboard — this is the decode that fixes it
H3's single-frame VAE won't load by itself — here's the loader that assembles it
The H3 VAE loader that exposes the tile size ComfyUI hides from you
Pin a strip of faces onto every frame of your video
Save the H3 latent without the native node crashing on it
H3's best frame isn't a fixed index — let Laplacian find it
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
Optional: pip install insightface with onnxruntime or onnxruntime-gpu, only for LTX Identity. The Shot Planner's
Find people / Cast no longer needs it (1.93.0): it uses OpenCV's YuNet + SFace (Apache-2.0, downloaded once), and uses
InsightFace only when it is installed. They are not in the requirements because insightface pins packages
that conflict with many environments; without them everything else works and those features say what to install.
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.
Shot Planner / Shot Loop (1.48.0)
Split a long video into shots a video model can follow (at camera cuts via PySceneDetect, fixed length, or by hand on a timeline), set a reference image and prompt per shot, run the rest of the workflow once per shot, and join the results back with the original timing and soundtrack.
- BFS Shot Planner — interactive timeline (thumbnails, cut detector curve, draggable boundaries, per-shot reference gallery and prompt). Outputs the shots as a ComfyUI list, so every node downstream runs once per shot.
- BFS Shot Unpack — guide frames, references, prompt and length of one shot, for any model.
- BFS Shot H3 Conditioning — MiniMax H3 conditioning for one shot with the native nodes (aligned guide and/or native reference video).
- BFS Shot Join — concatenates, trims to the true lengths, cross-fades soft joins, returns audio. With
comparisonon, itsguideoutput is the original video frame for frame. - BFS Video Compare — one player for two videos (Join's
guideandimages): wipe ↔ / ↕, overlay or side by side, any of guide / target / difference on top, plus a per-pixel difference map and the difference per frame (click to jump).
Cast (1.49.0): Find people tracks faces through the video (InsightFace) and groups them into people. Link each person to a reference and every shot uses the reference of the person with the most screen time in it; optionally split where the main person changes and run only the shots where a linked person appears.
Two run modes: auto loop (all shots in one run) and queue loop (one shot per run, stored on
disk, re-queued automatically; nodes after the join only run on the last shot). See
web/js/docs/BFSShotPlanner.md.
Shots can also be cropped to a SAM 3 mask (text or points per shot) and pasted back by the join, continue from the previous shot's result, and get VLM suggestions (what to segment, a shot description for the prompt, run/skip) from a Qwen3-VL connected to the planner.
H3 Duet / Side Panel (1.50.0)
Training-free split-screen generation for MiniMax H3 (TSC's latent pin): a panel (the source clip
or a reference) is pinned beside the video with a noise mask, the video is generated in sync with
it, and the panel is cropped off before decoding. BFS H3 Duet does it all in one node, BFS Shot H3 Duet renders each shot of the Shot Loop that way (or with an aligned guide for body-swap LoRAs);
BFS H3 Side Panel + BFS H3 Side Panel Crop are the building blocks. Optional aligned latent
guide. 1.84.0: panel_static (TV static over the face / person of the pinned clip, SAM 3) and a setting
picture (BFS Setting Picture) for same-world swaps. See web/js/docs/BFSH3Duet.md.
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.
MiniMax-H3 downscaled latent guides (1.46.0)
MiniMax-H3 Downscaled Latent Guide (BFS) supports aligned lower-resolution
image/video guides for H3 LoRAs trained with target_grid_stride_v1. It encodes
the smaller guide and patches only the returned model's packed coordinates.
Connect both its MODEL and positive CONDITIONING outputs to sampling.
MiniMax-H3 Guide Target — Image / Video (BFS) creates an exact output canvas: use one frame for images or 73 frames for approximately three seconds at 24 fps. At output 1024 x 768 and factor 4, the guide preview is 256 x 192.
See setup, workflow template, compatibility and validation.
BFSNodes 1.47.0 adds optional MiniMax-H3 overlap/sidecar source-phase RoPE and MiniMax-H3 Identity Reference + RoPE (BFS). See the H3 guide.