Danbooru FAISS Search Nodes

By l33chkingView on GitHub →

Use image to search similar images from danbooru using various methods. Notice: the optional API key will be saved to metadata if used

VRAM Requirements

Direct Answer: The ComfyUI node Danbooru FAISS Search Nodes 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 Danbooru FAISS Search Nodes requires installing the following Python package dependencies: beautifulsoup4>=4.11.0, dghs-imgutils>=0.4.8, faiss-cpu>=1.7.0, lxml>=4.9.0, numpy>=1.22.0, onnxruntime>=1.16.0 # required for ONNX tag encoder (clip_text/siglip_text), pillow>=9.0.0, requests>=2.28.0, timm>=0.9.12, torch>=1.12.0, torchvision>=0.13.0. This node specifically requires PyTorch version 1.12.0 or newer.

requirements.txt
beautifulsoup4>=4.11.0
dghs-imgutils>=0.4.8
faiss-cpu>=1.7.0
lxml>=4.9.0
numpy>=1.22.0
onnxruntime>=1.16.0  # required for ONNX tag encoder (clip_text/siglip_text)
pillow>=9.0.0
requests>=2.28.0
timm>=0.9.12
torch>=1.12.0
torchvision>=0.13.0

🛠️ 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 1.12.0+.

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