ComfyUI-FASHN-VTON

By drpheroView on GitHub →

Implements the FASHN VTON v1.5 model for virtual try-on in ComfyUI

How much VRAM does ComfyUI-FASHN-VTON require?

Direct Answer: The ComfyUI node ComfyUI-FASHN-VTON 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

What Python packages are required for ComfyUI-FASHN-VTON?

Direct Answer: Running ComfyUI-FASHN-VTON requires installing the following Python package dependencies: einops>=0.6.0, fashn-human-parser>=0.1.1, huggingface_hub>=0.20.0, matplotlib>=3.5.0, numpy>=1.21.0, onnxruntime-gpu, opencv-python>=4.5.0, pillow>=9.0.0, safetensors>=0.3.0, tqdm>=4.65.0. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
einops>=0.6.0
fashn-human-parser>=0.1.1
huggingface_hub>=0.20.0
matplotlib>=3.5.0
numpy>=1.21.0
onnxruntime-gpu
opencv-python>=4.5.0
pillow>=9.0.0
safetensors>=0.3.0
tqdm>=4.65.0

Interactive Setup & Dependency Resolver

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

Related Custom Nodes

The following custom nodes run in the same PyTorch / CUDA environment and share similar categories or workflows:

AAA Metadata System
by EricRollei128MB VRAM
Animatediff MotionLoRA Trainer
by kijai4.0GB VRAM
Arc2Face ComfyUI Node Library
by caleboleary128MB VRAM
Arthemy Live Tuner - SDXL
by aledelpho8.0GB VRAM
BokehDiffusionComfyUI
by jrabek256MB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI-FASHN-VTON require?

ComfyUI-FASHN-VTON requires a minimum of 128MB (0.1GB) of VRAM for base operation. For optimal performance, a GPU with at least 4GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.

Can I run ComfyUI-FASHN-VTON on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.3GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.5GB headroom

What Python packages are required for ComfyUI-FASHN-VTON?

To run ComfyUI-FASHN-VTON, you need to install: einops>=0.6.0, fashn-human-parser>=0.1.1, huggingface_hub>=0.20.0, matplotlib>=3.5.0, numpy>=1.21.0, onnxruntime-gpu, opencv-python>=4.5.0, pillow>=9.0.0, safetensors>=0.3.0, tqdm>=4.65.0. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI-FASHN-VTON?

ComfyUI-FASHN-VTON supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.

How do I install ComfyUI-FASHN-VTON in ComfyUI?

To install ComfyUI-FASHN-VTON: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/drphero/ComfyUI-FASHN-VTON, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.