ImageProcessing

By bvhariView on GitHub →

ComfyUI custom nodes to apply various image processing techniques.

How much VRAM does ImageProcessing require?

Direct Answer: The ComfyUI node ImageProcessing 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!

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

What Python packages are required for ImageProcessing?

Direct Answer: Running ImageProcessing requires installing the following Python package dependencies: kornia, torch. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
kornia
torch

Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

Related Custom Nodes

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

0x-jerry/Rembg Background Removal Node for ComfyUI
by 0x-jerry128MB VRAM
A8R8 ComfyUI Nodes
by ramyma128MB VRAM
AI4ArtsEd Nodes
by joeriben128MB VRAM
AIFSH/ComfyUI-AuraSR
by AIFSH128MB VRAM

Frequently Asked Questions

How much VRAM does ImageProcessing require?

ImageProcessing 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 ImageProcessing 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

What PyTorch version does ImageProcessing need?

ImageProcessing requires the following PyTorch-related packages: torch. 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 ImageProcessing?

To run ImageProcessing, you need to install: kornia, torch. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ImageProcessing?

ImageProcessing 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 ImageProcessing in ComfyUI?

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