ComfyUI-AutoLabel
ComfyUI-AutoLabel is a custom node for ComfyUI that uses BLIP (Bootstrapping Language-Image Pre-training) to generate detailed descriptions of the main object in an image. This node leverages the power of BLIP to provide accurate and context-aware captions for images. by Fexploit.
How much VRAM does ComfyUI-AutoLabel require?
Direct Answer: The ComfyUI node ComfyUI-AutoLabel requires a minimum base VRAM of 256MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 256MB (0.3GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- HIGH
Interactive VRAM Compatibility Estimator
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 Cloud GPUs
Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance cloud GPUs on RunPod instantly.
What Python packages are required for ComfyUI-AutoLabel?
Direct Answer: Running ComfyUI-AutoLabel requires installing the following Python package dependencies: accelerate>=0.12.0, datasets>=2.0.0, pillow>=8.0.0, sentencepiece>=0.1.96, torch>=1.10.0, transformers>=4.15.0. This node specifically requires PyTorch version 1.10.0 or newer.
accelerate>=0.12.0
datasets>=2.0.0
pillow>=8.0.0
sentencepiece>=0.1.96
torch>=1.10.0
transformers>=4.15.0Interactive Setup & Dependency Resolver
# Loading command...Special Environment Requirements:
Requires PyTorch version 1.10.0+.
# Loading PyTorch command...Frequently Asked Questions
How much VRAM does ComfyUI-AutoLabel require?
ComfyUI-AutoLabel requires a minimum of 256MB (0.3GB) 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-AutoLabel on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.2GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.4GB headroom
What PyTorch version does ComfyUI-AutoLabel need?
ComfyUI-AutoLabel requires the following PyTorch-related packages: torch>=1.10.0. 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 ComfyUI-AutoLabel?
To run ComfyUI-AutoLabel, you need to install: accelerate>=0.12.0, datasets>=2.0.0, pillow>=8.0.0, sentencepiece>=0.1.96, torch>=1.10.0, transformers>=4.15.0. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running ComfyUI-AutoLabel?
ComfyUI-AutoLabel 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-AutoLabel in ComfyUI?
To install ComfyUI-AutoLabel: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/fexploit/ComfyUI-AutoLabel, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.