ComfyUI-FaceKeypointsFilter

By smartvainView on GitHub →

ComfyUI custom node that selectively filters facial keypoints from DWPose/OpenPose output, allowing selective disabling of face parts (chin, eyebrows, eyes, nose, mouth outer/inner contours) for ControlNet workflows. (Description by CC)

How much VRAM does ComfyUI-FaceKeypointsFilter require?

Direct Answer: The ComfyUI node ComfyUI-FaceKeypointsFilter requires a minimum base VRAM of 2048MB and is optimized for GPUs with at least 6GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

High (2-4GB)
Base VRAM:
2048MB (2.0GB)
Recommended GPU:
6GB+ 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!

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Related Custom Nodes

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

A3D ComfyUI Integration
by n0neye256MB VRAM
AgaveLogicCounter
by agavesunset128MB VRAM
Anima Regional Canvas
by ukr8b3g-cmyk2.0GB VRAM
ComfyNodesPlus
by chemicalshock256MB VRAM
ComfyUI DeviantArt Sender
by sni10256MB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI-FaceKeypointsFilter require?

ComfyUI-FaceKeypointsFilter requires a minimum of 2048MB (2.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 6GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.

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

✅ RTX 3060 (12GB): Yes, fully compatible with 8.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 8.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 12.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 19.6GB headroom

How can I reduce VRAM usage when running ComfyUI-FaceKeypointsFilter?

ComfyUI-FaceKeypointsFilter 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-FaceKeypointsFilter in ComfyUI?

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