ComfyUI Batch BBox Detector

By rsloschView on GitHub →

Process batches of images (e.g., video frames) with ultralytics bbox detection in ComfyUI. This custom node package extends the standard BboxDetectorCombined to handle batches efficiently, making it ideal for processing 300+ video frames.

How much VRAM does ComfyUI Batch BBox Detector require?

Direct Answer: The ComfyUI node ComfyUI Batch BBox Detector requires a minimum base VRAM of 4096MB and is optimized for GPUs with at least 8GB of VRAM. Low VRAM mode is not supported for this node.

Very High (4-8GB)
Base VRAM:
4096MB (4.0GB)
Recommended GPU:
8GB+ VRAM
Low VRAM Mode:
✗ Not 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 Cloud GPUs

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Related Custom Nodes

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

APISR IN COMFYUI
by ZHO-ZHO-ZHO4.0GB VRAM
Avatar Graph
by avatechai128MB VRAM
CWK_Wan2.2_Nodes
by cowneko4.0GB VRAM
Comfy EverAnimate
by younestft128MB VRAM
ComfyUI Batch Blend
by starfieldscreensaver4.0GB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI Batch BBox Detector require?

ComfyUI Batch BBox Detector requires a minimum of 4096MB (4.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 8GB of VRAM is recommended. Low VRAM mode is not supported for this node.

Can I run ComfyUI Batch BBox Detector on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 10.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 17.6GB headroom

How do I install ComfyUI Batch BBox Detector in ComfyUI?

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