ComfyUI-MusePose-Remaster

By hoveychenView on GitHub →

MusePose Remaster is a remaster version of ComfyUI MusePose node. It supports auto weights download, remove most necessary dependencies, etc.

How much VRAM does ComfyUI-MusePose-Remaster require?

Direct Answer: The ComfyUI node ComfyUI-MusePose-Remaster 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 ComfyUI-MusePose-Remaster?

Direct Answer: Running ComfyUI-MusePose-Remaster requires installing the following Python package dependencies: accelerate==0.29.3, clip@ https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip#sha256=b5842c25da441d6c581b53a5c60e0c2127ebafe0f746f8e15561a006c6c3be6a, decord==0.6.0; sys_platform != 'darwin' and platform_machine != 'arm64', diffusers>=0.24.0,<=0.27.2, einops==0.4.1, eva-decord==0.6.1; sys_platform == 'darwin' and platform_machine == 'arm64', imageio==2.33.0, imageio-ffmpeg==0.4.9, moviepy==1.0.3, omegaconf==2.2.3, open-clip-torch==2.20.0, opencv-contrib-python==4.8.1.78, opencv-python==4.8.1.78, scikit-image==0.21.0, scikit-learn==1.3.2, torch, torchdiffeq, torchmetrics, torchsde, torchvision, transformers==4.33.1, urllib3==1.26.9, xformers. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
accelerate==0.29.3
clip@ https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip#sha256=b5842c25da441d6c581b53a5c60e0c2127ebafe0f746f8e15561a006c6c3be6a
decord==0.6.0; sys_platform != 'darwin' and platform_machine != 'arm64'
diffusers>=0.24.0,<=0.27.2
einops==0.4.1
eva-decord==0.6.1; sys_platform == 'darwin' and platform_machine == 'arm64'
imageio==2.33.0
imageio-ffmpeg==0.4.9
moviepy==1.0.3
omegaconf==2.2.3
open-clip-torch==2.20.0
opencv-contrib-python==4.8.1.78
opencv-python==4.8.1.78
scikit-image==0.21.0
scikit-learn==1.3.2
torch
torchdiffeq
torchmetrics
torchsde
torchvision
transformers==4.33.1
urllib3==1.26.9
xformers

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 ComfyUI-MusePose-Remaster require?

ComfyUI-MusePose-Remaster 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 ComfyUI-MusePose-Remaster 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 ComfyUI-MusePose-Remaster need?

ComfyUI-MusePose-Remaster requires the following PyTorch-related packages: open-clip-torch==2.20.0, torch, torchdiffeq, torchmetrics, torchsde, 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-MusePose-Remaster?

To run ComfyUI-MusePose-Remaster, you need to install: accelerate==0.29.3, clip@ https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip#sha256=b5842c25da441d6c581b53a5c60e0c2127ebafe0f746f8e15561a006c6c3be6a, decord==0.6.0; sys_platform != 'darwin' and platform_machine != 'arm64', diffusers>=0.24.0,<=0.27.2, einops==0.4.1, eva-decord==0.6.1; sys_platform == 'darwin' and platform_machine == 'arm64', imageio==2.33.0, imageio-ffmpeg==0.4.9, moviepy==1.0.3, omegaconf==2.2.3, open-clip-torch==2.20.0, opencv-contrib-python==4.8.1.78, opencv-python==4.8.1.78, scikit-image==0.21.0, scikit-learn==1.3.2, torch, torchdiffeq, torchmetrics, torchsde, torchvision, transformers==4.33.1, urllib3==1.26.9, xformers. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI-MusePose-Remaster?

ComfyUI-MusePose-Remaster 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-MusePose-Remaster in ComfyUI?

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