ComfyUI-Vton-Mask

By karthikg-09View on GitHub →

A lightweight ComfyUI custom node for generating high-quality masks and pose detection for virtual try-on applications. This node extracts only the essential masking functionality from FitDiT without requiring heavy diffusion models.

VRAM Requirements

Direct Answer: The ComfyUI node ComfyUI-Vton-Mask requires a minimum base VRAM of 128MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

High (2-4GB)
Base VRAM:
128MB (0.1GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
MEDIUM

🧮 Interactive VRAM Compatibility Estimator

Estimated Total VRAM: 3.00 GBTarget: 8 GB
✅ Comfortable Fit

Your GPU has plenty of headroom. You can run this node safely with your active configurations!

Deploy on High-Performance GPUs

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance GPUs on Vast.ai instantly.

🚀 Deploy on Vast.ai

Deploy on Cloud GPUs

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance cloud GPUs on RunPod instantly.

🚀 Deploy on RunPod

Python Dependencies

Direct Answer: Running ComfyUI-Vton-Mask requires installing the following Python package dependencies: huggingface_hub>=0.16.0, numpy>=1.21.0, onnxruntime>=1.8.0, opencv-python>=4.5.0, pillow>=8.0.0, scikit-image>=0.18.0, torch>=1.9.0, torchvision>=0.10.0, tqdm>=4.62.0, transformers>=4.20.0. This node specifically requires PyTorch version 1.9.0 or newer.

requirements.txt
huggingface_hub>=0.16.0
numpy>=1.21.0
onnxruntime>=1.8.0
opencv-python>=4.5.0
pillow>=8.0.0
scikit-image>=0.18.0
torch>=1.9.0
torchvision>=0.10.0
tqdm>=4.62.0
transformers>=4.20.0

🛠️ Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

⚠️ Special Environment Requirements:

Requires PyTorch version 1.9.0+.

To update PyTorch for your selected setup, run:
# Loading PyTorch command...