NormalMapLightEstimator
A ComfyUI custom node for estimating light direction and quality from normal maps using luma masking. The system analyzes surface normals to infer lighting information for downstream tasks like adaptive relighting, directional masking, or stylized effects.
How much VRAM does NormalMapLightEstimator require?
Direct Answer: The ComfyUI node NormalMapLightEstimator 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.
- Base VRAM:
- 128MB (0.1GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- MEDIUM
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
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What Python packages are required for NormalMapLightEstimator?
Direct Answer: Running NormalMapLightEstimator requires installing the following Python package dependencies: matplotlib>=3.7.0, numpy>=1.21.0, pillow>=8.0.0, torch>=1.9.0. This node specifically requires PyTorch version 1.9.0 or newer.
matplotlib>=3.7.0
numpy>=1.21.0
pillow>=8.0.0
torch>=1.9.0Interactive Setup & Dependency Resolver
# Loading command...Special Environment Requirements:
Requires PyTorch version 1.9.0+.
# Loading PyTorch command...Frequently Asked Questions
How much VRAM does NormalMapLightEstimator require?
NormalMapLightEstimator 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 NormalMapLightEstimator 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 NormalMapLightEstimator need?
NormalMapLightEstimator requires the following PyTorch-related packages: torch>=1.9.0. 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 NormalMapLightEstimator?
To run NormalMapLightEstimator, you need to install: matplotlib>=3.7.0, numpy>=1.21.0, pillow>=8.0.0, torch>=1.9.0. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running NormalMapLightEstimator?
NormalMapLightEstimator 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 NormalMapLightEstimator in ComfyUI?
To install NormalMapLightEstimator: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/APZmedia/Comfyui-LightDirection-estimation, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.