Skin Tone Detector for ComfyUI

By kevinmcmahondevView on GitHub →

A ComfyUI node that detects the skin tone of a person in an image and matches it to the standard emoji skin tone palette.

How much VRAM does Skin Tone Detector for ComfyUI require?

Direct Answer: The ComfyUI node Skin Tone Detector for ComfyUI 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

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🚀 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 Skin Tone Detector for ComfyUI?

Direct Answer: Running Skin Tone Detector for ComfyUI requires installing the following Python package dependencies: face-recognition, mediapipe, numpy, opencv-python, pillow, scikit-image, torch. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
face-recognition
mediapipe
numpy
opencv-python
pillow
scikit-image
torch

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:

ComfyUI-Light-N-Color
by KAVVATARE128MB VRAM
4dgs-human-avatar-comfyui-nodes-dataset
by AndriiShramko4.0GB VRAM
AAA Metadata System
by EricRollei128MB VRAM
AMD Video Upscaler
by yasei-no-otoko3.0GB VRAM

Frequently Asked Questions

How much VRAM does Skin Tone Detector for ComfyUI require?

Skin Tone Detector for ComfyUI 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 Skin Tone Detector for ComfyUI 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 PyTorch version does Skin Tone Detector for ComfyUI need?

Skin Tone Detector for ComfyUI requires the following PyTorch-related packages: torch. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).

What Python packages are required for Skin Tone Detector for ComfyUI?

To run Skin Tone Detector for ComfyUI, you need to install: face-recognition, mediapipe, numpy, opencv-python, pillow, scikit-image, torch. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running Skin Tone Detector for ComfyUI?

Skin Tone Detector for ComfyUI 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 Skin Tone Detector for ComfyUI in ComfyUI?

To install Skin Tone Detector for ComfyUI: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/kevinmcmahondev/comfyui-skin-tone-detector, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.