Qwen Layers Diffuser Pipeline

By EricRolleiView on GitHub →

Decompose images into semantic RGBA layers using Qwen-Image-Layered model. Features AI-powered layer naming, PSD/TIFF export with proper layer structure, original resolution support, and VRAM management. Includes 18 nodes for layer decomposition, manipulation, and saving.

How much VRAM does Qwen Layers Diffuser Pipeline require?

Direct Answer: The ComfyUI node Qwen Layers Diffuser Pipeline 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!

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What Python packages are required for Qwen Layers Diffuser Pipeline?

Direct Answer: Running Qwen Layers Diffuser Pipeline requires installing the following Python package dependencies: numpy, pillow>=9.0.0, psd-tools>=1.9.0, tifffile>=2023.0.0, torch. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
numpy
pillow>=9.0.0
psd-tools>=1.9.0
tifffile>=2023.0.0
torch

Interactive Setup & Dependency Resolver

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

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Frequently Asked Questions

How much VRAM does Qwen Layers Diffuser Pipeline require?

Qwen Layers Diffuser Pipeline 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 Qwen Layers Diffuser Pipeline 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 Qwen Layers Diffuser Pipeline need?

Qwen Layers Diffuser Pipeline 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 Qwen Layers Diffuser Pipeline?

To run Qwen Layers Diffuser Pipeline, you need to install: numpy, pillow>=9.0.0, psd-tools>=1.9.0, tifffile>=2023.0.0, torch. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running Qwen Layers Diffuser Pipeline?

Qwen Layers Diffuser Pipeline 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 Qwen Layers Diffuser Pipeline in ComfyUI?

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