torch omegaconf

MatAnyone in ComfyUI (Remove background)
Stable Video Matting with Consistent Memory Propagation:
Scaling Video Matting via a Learned Quality Evaluator:
Download matanyone.pth from
Download matanyone2.pth from
checkpoint/
matanyone.pth
matanyone2.pth
https://github.com/user-attachments/assets/f1805028-92ed-40b7-8bf5-85f1a3ddbe25
The extension now includes the MatAnyone2Video node, which runs the improved MatAnyoneV2 model for higher-quality and more robust video matting.
Workflow: workflow/workflow_mat_anyone.json
(Not a workflow-embedded image)
Inputs:
forground_mask (IMAGE) or foreground_MASK (MASK): The input mask. IMAGE option will automatically convert a black/white image to a mask. At least one option must be given.solid_color (optional): The solid color to create a screen. Defaults to Green Screen.mask_frame: The input mask’s index (defaults to 0). Support first (0), last and middle frame.n_warmup: Number of iterations to warm up the model. Defaults to 10.Memory Management Inputs:
max_internal_size (optional): Resizes the internal processing resolution to save memory (e.g., 360, 480). Default is -1 (full resolution).max_mem_frames (optional): The number of key frames kept in high-resolution working memory. Default is 5.use_long_term (optional): Limits active memory scaling by compressing older frames into long-term prototype memories, preventing OOM over time. Default is False. (Useful for long videos)Your input mask won’t actually be in the final matte. Instead, the warmup process generate a new input mask, which is then propagated throughout the video.
Additional Inputs for V2:
r_erode (optional): The radius for morphological erosion applied to the foreground_mask before processing (defaults to 0). Useful for refining rough masks.r_dilate (optional): The radius for morphological dilation applied to the foreground_mask before processing (defaults to 0).@InProceedings{yang2025matanyone,
title = {{MatAnyone}: Stable Video Matting with Consistent Memory Propagation},
author = {Yang, Peiqing and Zhou, Shangchen and Zhao, Jixin and Tao, Qingyi and Loy, Chen Change},
booktitle = {arXiv preprint arXiv:2501.14677},
year = {2025}
}
@InProceedings{yang2026matanyone2,
title = {{MatAnyone 2}: Scaling Video Matting via a Learned Quality Evaluator},
author = {Yang, Peiqing and Zhou, Shangchen and Hao, Kai and Tao, Qingyi},
booktitle = {CVPR},
year = {2026}
}