Extensions/ComfyUI-MiniMax-Remover
ComfyUI Extension

ComfyUI-MiniMax-Remover

ComfyUI-MiniMax-Remover is a custom node for ComfyUI that enables fast and efficient object removal using minimax optimization. It works in two stages: first, it trains…

By 1038lab·Created about a year ago·Updated about a year ago· 90
1038lab/ComfyUI-MiniMax-Remover
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Stars90
Updatedabout a year ago
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ComfyUI MiniMax-Remover

A ComfyUI custom node for fast and effective video/image object removal using MiniMax optimization. Remove objects from videos and images with high quality results using only 6-12 inference steps.

✨ Features

  • 🚀 Fast: Only 6-12 inference steps required, no CFG needed
  • 🎯 Effective: Seamlessly removes objects from videos and images
  • 💪 Robust: Prevents regeneration of unwanted objects or artifacts
  • 🔧 Easy to Use: Simple ComfyUI nodes with intuitive workflows
  • 📱 Flexible: Supports both single images and video processing
  • ⚡ Optimized: Automatic model downloading and caching
  • 💡 Smart Hints: Automatic backend suggestions for optimal settings

Image subject Remover

🛠️ Installation

Method 1: ComfyUI Manager (Recommended)

  1. Open ComfyUI Manager
  2. Search for "MiniMax-Remover"
  3. Click Install
  4. Restart ComfyUI

Method 2: Manual Installation

  1. Navigate to your ComfyUI custom_nodes directory:
cd ComfyUI/custom_nodes
  1. Clone this repository:
git clone https://github.com/1038lab/ComfyUI-MiniMax-Remover.git
  1. Install dependencies:
cd ComfyUI-MiniMax-Remover

For Portable ComfyUI (Windows):

..\..\..\python_embeded\python.exe -m pip install -r requirements.txt

For Standard Python Installation:

pip install -r requirements.txt
  1. Restart ComfyUI

📥 Model Download

Models will be automatically downloaded from HuggingFace when first used.

Manual Model Download (Optional)

If automatic download fails or you prefer manual installation:

  1. Download using HuggingFace CLI:
huggingface-cli download zibojia/minimax-remover --include vae transformer scheduler --local-dir ./models/MiniMax-Remover
  1. Or download manually from HuggingFace:

    • Visit: https://huggingface.co/zibojia/minimax-remover
    • Download the vae, transformer, and scheduler folders
    • Place them in: ComfyUI/models/MiniMax-Remover/
  2. Verify installation:

    • Check that ComfyUI/models/MiniMax-Remover/ contains:
      • vae/ folder
      • transformer/ folder
      • scheduler/ folder

📦 Available Nodes

| Node Name | Display Name | Purpose | |-----------|--------------|---------| | MinimaxImageRemover | MiniMax Image Object Remover | Remove objects from single images (requires external model loader) | | MinimaxVideoRemover | MiniMax Video Object Remover | Remove objects from videos (requires external model loader) | | MinimaxModelLoader | MiniMax Model Loader | Load VAE, Transformer, and Scheduler for separate nodes | | MinimaxVideoLoader | MiniMax Video Loader | Load video files for processing | | ImageSizeAdjuster | MiniMax Image Size Adjuster | Adjust image dimensions for compatibility |

⚙️ Recommended Settings

MiniMax Model Loader (Advanced)

  • scheduler_type: FlowMatchEulerDiscreteScheduler (recommended) or UniPCMultistepScheduler
  • torch_dtype: float16 (GPU recommended) or float32 (CPU/compatibility)
  • device: auto (automatic detection)

🎨 Mask Requirements

Supported Formats

  • Grayscale images (recommended)
  • RGB images (automatically converted)
  • PNG, JPG, TIFF and other common formats

Mask Guidelines

  • Black background, white foreground (standard mask format)
  • High contrast for better edge detection
  • Complete coverage of objects to remove
  • Clean edges without excessive noise
  • Avoid overly complex details in small areas

🚀 Performance Tips

GPU Memory Optimization

  1. Use float16 precision (reduces memory by ~50%)
  2. Keep image resolution reasonable (≤1024x1024 recommended)
  3. Use fewer inference steps (6-12 usually sufficient)
  4. Close other GPU applications to free VRAM

Processing Speed

  1. FlowMatchEulerDiscreteScheduler is typically faster than UniPCMultistepScheduler
  2. temporal_frames=3 provides best speed/quality balance
  3. Use ImageSizeAdjuster node to optimize image dimensions for better performance

🔧 Requirements

System Requirements

  • Python: 3.8 or higher
  • GPU: NVIDIA GPU with CUDA support (recommended)
  • RAM: 8GB+ system RAM
  • VRAM: 6GB+ GPU memory for optimal performance

Dependencies

All dependencies are automatically installed via requirements.txt:

torch>=1.13.0
diffusers>=0.21.0
decord>=0.6.0
einops>=0.6.0
scipy>=1.9.0
opencv-python>=4.5.0
huggingface_hub>=0.16.0
accelerate>=0.20.0

❓ Troubleshooting

Common Issues

Model Download Fails

  • Try manual download from HuggingFace website
  • Check internet connection and HuggingFace access
  • Ensure sufficient disk space in ComfyUI/models/MiniMax-Remover/

CUDA Out of Memory

  • Reduce image resolution
  • Use float16 instead of float32
  • Reduce num_inference_steps
  • Close other applications using GPU

Tensor Dimension Errors

  • Ensure mask and image have compatible dimensions
  • Enable fix_dimensions in the All-in-One node for automatic adjustment
  • Use ImageSizeAdjuster node for manual dimension control
  • Check that images are RGB (not RGBA)

Dimension Warning Messages

  • If you see "Image dimensions not divisible by 16" warning, enable fix_dimensions=True
  • The All-in-One node will automatically suggest this when needed

Poor Removal Quality

  • Increase num_inference_steps (try 16-20)
  • Improve mask quality (higher contrast, cleaner edges)
  • Adjust mask_dilation_iterations based on mask precision
  • Try different scheduler types

📚 Additional Resources

📄 License

License Python ComfyUI

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.

🙏 Acknowledgments

  • MiniMax-Remover Team for the original research and implementation
  • ComfyUI Community for the excellent framework and ecosystem
  • HuggingFace for model hosting and distribution
  • Contributors who helped improve this custom node

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

⭐ Support

If you find this project helpful, please consider giving it a star on GitHub! It helps others discover the project and motivates continued development.


Made with ❤️ for the ComfyUI community