Lightricks / LTX-2.5-22b-IC-LoRA-Alpha-Gen

LTX-2.5 22B IC-LoRA Alpha Gen

This is an Alpha Gen IC-LoRA trained on top of LTX-2.5-22B . It takes an ordinary RGB ("beauty") video and generates a matching alpha matte for it, with no green screen, masks, or prompt required. It handles hard subjects as well as soft and semi-transparent elements such as hair, fur, smoke, fire, sheer fabric, glass, and water.

It is based on the LTX-2.5 foundation model.

Model Files

ltx-2.5-22b-ic-lora-alpha-gen-0.9.safetensors : the released checkpoint (training step 25000). Recommended inference on the -distilled base.

Model Details

• Base Model: LTX-2.5-22B Video
• Training Type: IC-LoRA (video-to-video, reference-conditioned)
• Control Type: Reference video: the RGB clip to be matted. The model outputs a grayscale alpha matte (white = foreground, black = background) aligned frame-for-frame with the input.
• Reference Downscale Factor: 1 (the reference is processed at the same resolution as the output).
• Prompt: Always empty. The RGB video is the only guide.

Intended Use & Out-of-Scope

Intended use: Pulling an alpha matte from live-action or generated footage for compositing and VFX: isolating people, animals, objects, logos, and characters so they can be placed over new backgrounds, including shots with soft or semi-transparent edges that are hard to key or rotoscope.

Out of scope: Clips longer than 145 frames : above that, RGB content starts leaking into the matte, so trim or split longer clips. Resolutions above 1920×1088 . Choosing which object to matte: there is no prompt or mask control, and the model decides the foreground on its own.

Control Signal Requirements

• Control signal type: The RGB clip to be matted (the "beauty" pass).
• Expected input: A single video at up to 1920×1088 and up to 145 frames.
• Preprocessing: Pad (don't stretch) the clip to dimensions divisible by 32 and a frame count of 8n+1 (e.g. 1920×1080 → 1920×1088; 145 frames already fits). No extractor or normalization is needed; the RGB clip is VAE-encoded directly.
• Alignment: The matte is generated at the same size and length as the reference and is frame-aligned with it.
• Mask support: Not supported. The model predicts the foreground for the whole frame.

How It Works

The IC-LoRA conditions on the latents of the RGB reference video and generates the corresponding alpha matte as a video, with an empty text prompt . Because the reference stays attached for the entire denoise (stage-1-only inference at native resolution), the matte stays aligned with the source down to fine edges.

To composite, use the matte as the alpha channel of the original RGB clip:

out = rgb * alpha + background * (1 - alpha)

Usage

🔌 ComfyUI

1. Copy ltx-2.5-22b-ic-lora-alpha-gen-0.9.safetensors into models/loras .
2. Load the LTX-2.5-22B distilled base model and add the LoRA.
3. Use the IC-LoRA (video-to-video) workflow from the LTX-2 ComfyUI repository . Select this LoRA in the IC-LoRA loader node, connect your RGB clip as the reference video, and leave the prompt empty .
4. Use LoRA strength 1.0 .
5. The output video is the alpha matte. Combine it with your original clip as its alpha channel (e.g. in your compositor, or export RGBA / ProRes 4444).

Python pipeline

Use the IC-LoRA video-to-video pipeline ( python -m ltx_pipelines.ic_lora ) from LTX-2 with an empty prompt, --skip-stage-2 , and --width / --height set to 2× the source size , so the stage-1 render comes back at native resolution:

# --width/--height are 2x the 1920x1088 source: stage 1 renders at half the requested size
# and --skip-stage-2 skips the 2x upscale, so the matte comes out at 1920x1088.
python -m ltx_pipelines.ic_lora \
  --transformer-path ltx-2.5-22b-distilled-transformer-bf16.safetensors \
  --text-encoder-path gemma4-12b-with-proj-ltx-2.5-bf16.safetensors \
  --video-vae-path ltx-2.5-video-vae-bf16.safetensors \
  --audio-vae-path ltx-2.5-audio-vae-bf16.safetensors \
  --spatial-upsampler-path ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0.safetensors \
  --prompt "" \
  --width 3840 --height 2176 --num-frames 121 --frame-rate 24 \
  --video-conditioning input_1920x1088.mp4 1.0 \
  --lora ltx-2.5-22b-ic-lora-alpha-gen-0.9.safetensors 1.0 \
  --skip-stage-2 \
  --seed 1234 \
  --output-path matte.mp4

Recommended Settings

Tips & Troubleshooting

• RGB bleeding into the matte: the clip is too long. Keep it at 145 frames or fewer, and split longer shots into chunks.
• Out-of-memory: full-HD 145-frame clips need an H100/B200-class GPU. Shorten the clip or lower the resolution.
• Don't prompt: the model was built for an empty prompt; adding text doesn't steer which object is matted.

References

• Code: GitHub Repository
• ComfyUI: ComfyUI-LTXVideo
• IC-LoRA docs: IC-LoRA usage guide

License

See the LTX-2-community-license for full terms.

Acknowledgments

• Base model by Lightricks
• Training infrastructure: LTX-2 Community Trainer