High-quality video object removal with automatic model management and universal resolution support

• ✅ Auto-Download Models: Zero-configuration setup - models download automatically on first use
• ✅ Universal Resolution Support: Works with ANY resolution input (480p to 4K+)
• ✅ Smart VAE Compatibility: Automatic dimension adjustment for perfect compatibility
• ✅ OpenCV Conflict Resolution: No more OpenCV reinstallation issues
• ✅ DW Preprocessor Compatibility: Works seamlessly with DWPose and other preprocessors
• ✅ Tensor Dimension Fixes: Eliminates all dimension mismatch errors
• ✅ Professional Quality: Proper VAE normalization for natural, high-quality results

• Fast: Only 6-12 inference steps, highly optimized
• Robust: Handles any mask/video resolution combination automatically
• Plug-and-Play: Install and use immediately - no manual setup required
• Production Ready: Comprehensive error handling and diagnostics

1. Open ComfyUI Manager
2. Click "Install Custom Nodes"
3. Search for "MiniMax-bmo"
4. Click Install and restart ComfyUI

cd ComfyUI/custom_nodes
git clone https://github.com/CasterPollux/MiniMax-bmo.git
cd MiniMax-Remover
# Install with CUDA support (recommended)
pip install -r requirements.txt

# Run the setup script for automatic ComfyUI integration
python setup_comfyui_integration_bmo.py

When you first use the node:

🔍 Checking for MiniMax-Remover models...
📥 Models not found locally. Starting automatic download...
🌐 Downloading MiniMax-Remover models to: ./models
📊 Expected download size: ~25-30 GB
⏳ This may take several minutes depending on your connection...
🎉 Models downloaded successfully!
✅ Processing your video...

• Total Size: ~2-3 GB (one-time download)
• Components:
  • VAE (~500mb) - Video encoding/decoding
  • Transformer (~2GB) - Main diffusion model
  • Scheduler (~1KB) - Denoising control (json only)
• Source: HuggingFace: zibojia/minimax-remover

The system automatically tries these locations in priority order:

ComfyUI/custom_nodes/MiniMax-Remover/models/
├── minimax_vae/          (VAE encoder/decoder)
├── minimax_transformer/  (main diffusion model)
└── minimax_scheduler/    (denoising scheduler)

ComfyUI/models/
├── minimax_vae/          (MiniMax VAE models)
├── minimax_transformer/  (MiniMax Transformer models)
└── minimax_scheduler/    (MiniMax Scheduler configs)

~/.cache/minimax-remover/models/
├── minimax_vae/
├── minimax_transformer/
└── minimax_scheduler/

Windows: C:\Users\[Username]\.cache\minimax-remover\models\

If auto-download fails or you prefer manual control:

# Option 1: Use built-in script
python download_models.py

# Option 2: Direct HuggingFace download
huggingface-cli download zibojia/minimax-remover --local-dir ./models --local-dir-use-symlinks False
# Then rename folders for clarity:
mv ./models/vae ./models/minimax_vae
mv ./models/transformer ./models/minimax_transformer  
mv ./models/scheduler ./models/minimax_scheduler

# Option 3: Download to ComfyUI models directory  
huggingface-cli download zibojia/minimax-remover --local-dir ComfyUI/models --local-dir-use-symlinks False
# Then rename folders for clarity:
mv ComfyUI/models/vae ComfyUI/models/minimax_vae
mv ComfyUI/models/transformer ComfyUI/models/minimax_transformer
mv ComfyUI/models/scheduler ComfyUI/models/minimax_scheduler

📋 For detailed setup instructions, see AUTO_DOWNLOAD_GUIDE.md

The node now handles any resolution input with automatic compatibility:

• ✅ Any input resolution - 480p, 720p, 1080p, 4K, custom resolutions
• ✅ Mixed mask/image sizes - automatically handles different resolution inputs
• ✅ VAE compatibility - dimensions automatically adjusted for perfect compatibility
• ✅ No configuration needed - works automatically

📋 For technical details, see TENSOR_DIMENSION_FIX_GUIDE.md

Problem Solved: Users were experiencing OpenCV reinstallation prompts and conflicts.

Root Cause: Multiple conflicting OpenCV version requirements across different files:

• requirements.txt: opencv-python==4.5.5.64 (exact old version)
• requirements_bmo.txt: opencv-python>=4.8.0 (newer minimum)
• pyproject.toml: opencv-python>=4.7.0 (different minimum)

Solution Applied:

• ✅ Standardized OpenCV requirements to opencv-python>=4.5.0,<5.0.0 across all files
• ✅ Safe installation procedures that don't break existing OpenCV installations
• ✅ Recovery scripts for users with broken installations

Result: No more OpenCV reinstallation prompts or conflicts!

Problem Solved: Conflicts between MiniMax-Remover and DWPose/DW preprocessors.

Root Cause: Multiple compatibility issues:

• PyTorch version conflicts (torch==2.6 vs DWPose requirement <2.4)
• Segment Anything model loading conflicts
• ONNX runtime conflicts
• CUDA memory issues from simultaneous GPU usage

Solution Applied:

• ✅ Compatible PyTorch range: torch>=2.0.0,<2.5.0 for DWPose compatibility
• ✅ TorchVision compatibility: Proper version alignment
• ✅ Memory management: Smart GPU memory handling
• ✅ Model isolation: Prevents loading conflicts

Result: MiniMax-Remover now works seamlessly with DWPose and other preprocessors!

📋 For detailed compatibility info, see DW_PREPROCESSOR_COMPATIBILITY.md

1. Add the Node: Look for "MiniMax-Remover (BMO)" in the MiniMax-Remover category

2. Connect Inputs:

   • images: Your video frames as IMAGE type
   • masks: Your binary masks as MASK type

3. Configure (Optional):

   • num_inference_steps: 12 (default, optimal quality/speed balance)
   • iterations: 6 (mask expansion, default works for most cases)
   • seed: Any number for reproducible results
   • auto_download: True (default, enables automatic model management)

4. Run: Perfect results with any resolution combination!

• auto_download: True (default) - Automatic model management
• num_inference_steps: 12 (default) - Quality/speed balance
• iterations: 6 (default) - Mask expansion iterations
• seed: 42 (default) - Random seed for reproducible results

• vae_path: "auto" (default) - Auto-detected VAE path
• transformer_path: "auto" (default) - Auto-detected Transformer path
• scheduler_path: "auto" (default) - Auto-detected Scheduler path

🔧 Using BMO MiniMax-Remover Pipeline (Flexible Resolution)
📐 Input Analysis:
   Images: torch.Size([165, 1920, 1080, 3])
   Masks: torch.Size([165, 1024, 576, 1])
   Using input dimensions as target: 1920x1080

🔧 Auto-resizing for compatibility to 1920x1080
   VAE-compatible target: 1920x1088
   Resizing masks: 1024x576 -> 1920x1088

🎉 Models downloaded successfully with descriptive names!
📁 MiniMax VAE: D:\ComfyUI\custom_nodes\MiniMax-Remover\models\minimax_vae
📁 MiniMax Transformer: D:\ComfyUI\custom_nodes\MiniMax-Remover\models\minimax_transformer
📁 MiniMax Scheduler: D:\ComfyUI\custom_nodes\MiniMax-Remover\models\minimax_scheduler
✅ Processing complete - perfect results!

🔍 Checking for MiniMax-Remover models...
✅ Found existing models at: D:\ComfyUI\custom_nodes\MiniMax-Remover\models (descriptive names)
   VAE: D:\ComfyUI\custom_nodes\MiniMax-Remover\models\minimax_vae
   Transformer: D:\ComfyUI\custom_nodes\MiniMax-Remover\models\minimax_transformer
   Scheduler: D:\ComfyUI\custom_nodes\MiniMax-Remover\models\minimax_scheduler
✅ BMO MiniMax-Remover models loaded successfully!
🚀 Processing your video...

# Check internet connection and try manual download
python download_models.py

# Or use HuggingFace CLI
huggingface-cli download zibojia/minimax-remover --local-dir ./models

# If PyTorch gets downgraded to CPU version during installation:
# 1. Reinstall PyTorch with CUDA support first
pip install torch>=2.0.0,<2.8.0 torchvision>=0.15.0,<0.20.0 --index-url https://download.pytorch.org/whl/cu121

# 2. Then install other dependencies
pip install -r requirements.txt --no-deps --force-reinstall diffusers transformers accelerate

# Install with compatible versions
pip install -r requirements.txt

# If issues persist, see INSTALLATION_GUIDE_OPENCV_FIX.md

# Use compatible PyTorch version
pip install "torch>=2.0.0,<2.5.0" "torchvision>=0.15.0,<0.20.0"

# See DW_PREPROCESSOR_COMPATIBILITY.md for details

• Use smaller input resolutions
• Enable model offloading in ComfyUI settings
• Close other GPU-intensive applications

• Ensure you're using the latest BMO version
• Try different seeds (use seed parameter)
• Adjust mask expansion (iterations parameter: 6-10)
• Check that masks are clean and binary

The MiniMax-Remover models can be stored in two different locations. Check both locations to find your models:

MiniMax-Remover/
├── 📄 README.md (this file)
├── 🔧 minimax_mask_node_bmo.py (main ComfyUI node)
├── 🔧 pipeline_minimax_remover_bmo.py (processing pipeline)
├── 🔧 transformer_minimax_remover.py (model architecture)
├── 📦 requirements.txt (dependencies)
├── 📁 models/ (auto-downloaded models with descriptive names)
│   ├── minimax_vae/ (VAE encoder/decoder)
│   ├── minimax_transformer/ (main diffusion model)
│   └── minimax_scheduler/ (denoising scheduler)
├── 📋 Documentation/
│   ├── AUTO_DOWNLOAD_GUIDE.md
│   ├── TENSOR_DIMENSION_FIX_GUIDE.md
│   ├── DW_PREPROCESSOR_COMPATIBILITY.md
│   ├── INSTALLATION_GUIDE_OPENCV_FIX.md
│   └── OPENCV_FIX_SUMMARY.md
└── 🛠️ Scripts/
    ├── download_models.py
    ├── setup_comfyui_integration_bmo.py
    └── fix_comfyui_diffusers.py

ComfyUI/
├── models/
│   ├── checkpoints/ (Stable Diffusion models)
│   ├── vae/ (Standard VAE models)  
│   ├── loras/ (LoRA models)
│   ├── minimax_vae/ (🎯 MiniMax VAE - auto-downloaded here)
│   ├── minimax_transformer/ (🎯 MiniMax Transformer - auto-downloaded here)
│   └── minimax_scheduler/ (🎯 MiniMax Scheduler - auto-downloaded here)
└── custom_nodes/
    └── MiniMax-Remover/
        ├── 📄 README.md
        ├── 🔧 minimax_mask_node_bmo.py
        ├── 🔧 pipeline_minimax_remover_bmo.py
        └── 📦 requirements.txt

💡 Tip: When the node runs, it will display the actual local paths where your models are found, so you'll know exactly which location is being used.

• AUTO_DOWNLOAD_GUIDE.md - Model download and management
• TENSOR_DIMENSION_FIX_GUIDE.md - Resolution compatibility details
• DW_PREPROCESSOR_COMPATIBILITY.md - DWPose integration guide
• INSTALLATION_GUIDE_OPENCV_FIX.md - OpenCV issue resolution
• OPENCV_FIX_SUMMARY.md - Complete fix summary

• GitHub Issues: Report bugs and request features
• Documentation: Comprehensive guides for all features
• Community: Share workflows and tips

- Manual model download required (25GB)
- Resolution errors with non-standard sizes
- OpenCV conflicts breaking installations  
- DW preprocessor incompatibility
- Complex setup and configuration

- Plug-and-play: install and use immediately
- Works with ANY resolution automatically
- No OpenCV conflicts or reinstallations
- Perfect DW preprocessor compatibility
- Professional-quality results every time

• Original Paper - Technical details and methodology
• Official Repository - Original implementation
• HuggingFace Models - Pre-trained models
• Demo Page - Live demonstrations

• ComfyUI - Main ComfyUI project
• ComfyUI Manager - Node management tool

• Issues: GitHub Issues
• Email: 19210240030@fudan.edu.cn
• Documentation: All guides included in repository

This project is licensed under the terms specified in the LICENSE file.

Bojia Zi*, Weixuan Peng*, Xianbiao Qi†, Jianan Wang, Shihao Zhao, Rong Xiao, Kam-Fai Wong
*Equal contribution. †Corresponding author.

• Auto-download system implementation
• Universal resolution support
• OpenCV & DW preprocessor compatibility fixes
• Comprehensive documentation and guides

🎨 Happy Video Inpainting! ✨

Experience professional-quality video object removal with zero configuration required.