ComfyUI-DisPose
ComfyUI supports over lihxxx/DisPose, which generates a new video with a reference video as poses and a reference image as everything else.
Quick Technical Summary: ComfyUI-DisPose
- Base VRAM Footprint:
- 4096 MB (8 GB Tier)
- Primary Dependencies:
- accelerate, av, decord, diffusers, einops, huggingface_hub, imageio, matplotlib, numpy, omegaconf, onnxruntime, opencv_contrib_python, pillow, scipy, torch, torchvision, transformers
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/bombax-xiaoice/ComfyUI-DisPose
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does ComfyUI-DisPose require?
Direct Answer: The ComfyUI node ComfyUI-DisPose requires a minimum base VRAM of 4096MB and is optimized for GPUs with at least 8GB of VRAM. Low VRAM mode is not supported for this node.
- Base VRAM:
- 4096MB (4.0GB)
- Recommended GPU:
- 8GB+ VRAM
- Low VRAM Mode:
- ✗ Not supported
- Estimation Confidence:
- MEDIUM
Cheapest VRAM Upgrade Paths (Live Market Prices):
- GeForce RTX 3060 12GB (Ultimate Budget VRAM King)──► Used: $209.62View eBay ↗
- GeForce RTX 4060 8GB (Modern Entry-Level)──► New: $303.50View Amazon ↗
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
Verify Compatibility for Your Specific GPU VRAM
Select your graphics card's VRAM capacity to view optimized batch sizes, suggested resolutions, and custom performance tips for ComfyUI-DisPose:
Buy NVIDIA GeForce RTX 3060 (12GB VRAM)
Tired of renting cloud rigs? Run ComfyUI locally with absolute zero latency. Best entry-level ComfyUI experience. Avoids immediate VRAM limitations on basic LoRA training.
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What Python packages are required for ComfyUI-DisPose?
Direct Answer: Running ComfyUI-DisPose requires installing the following Python package dependencies: accelerate, av, decord, diffusers, einops, huggingface_hub, imageio, matplotlib, numpy, omegaconf, onnxruntime, opencv_contrib_python, pillow, scipy, torch, torchvision, transformers. Ensure your ComfyUI environment has these packages active before launching.
accelerate
av
decord
diffusers
einops
huggingface_hub
imageio
matplotlib
numpy
omegaconf
onnxruntime
opencv_contrib_python
pillow
scipy
torch
torchvision
transformersInteractive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does ComfyUI-DisPose require?
ComfyUI-DisPose requires a minimum of 4096MB (4.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 8GB of VRAM is recommended. Low VRAM mode is not supported for this node.
Can I run ComfyUI-DisPose on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 10.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 17.6GB headroom
How much VRAM does ComfyUI-DisPose take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), ComfyUI-DisPose runs smoothly on an RTX 3060 (12GB) with 6.8GB of headroom. This is sufficient to run the node alongside standard SD 1.5 and SDXL workflows in full precision. On an RTX 4090 (24GB VRAM), the node runs with extreme headroom on an RTX 4090 (24GB) with 17.6GB of dedicated headroom. This allows you to combine the node with massive models (like FLUX.1 Dev, Schnell, or Hunyuan Video) in full precision (FP16) without any offload flags.
What PyTorch version does ComfyUI-DisPose need?
ComfyUI-DisPose requires the following PyTorch-related packages: torch, torchvision. 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-DisPose?
To run ComfyUI-DisPose, you need to install: accelerate, av, decord, diffusers, einops, huggingface_hub, imageio, matplotlib, numpy, omegaconf, onnxruntime, opencv_contrib_python, pillow, scipy, torch, torchvision, transformers. You can install these using pip or add them to your requirements.txt file.
How do I install ComfyUI-DisPose in ComfyUI?
To install ComfyUI-DisPose: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/bombax-xiaoice/ComfyUI-DisPose, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.