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requirements.txt
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# ============================================
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#
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# MatAnyone (BEST) + SAM2 (VIDEO) + Rembg (FAST)
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# Optimized for HuggingFace Spaces L4 GPU
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# ============================================
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# Core Dependencies
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streamlit==1.32.2
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opencv-python-headless==4.8.1.78
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opencv-contrib-python==4.8.1.78
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numpy==1.26.4
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Pillow==10.2.0
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nvidia-ml-py==12.535.161
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py3nvml==0.2.7
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# PyTorch
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torch
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torchvision==0.17.0
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torchaudio==2.2.0
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# ============================================
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# PRIMARY
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# ============================================
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git+https://github.com/pq-yang/MatAnyone.git
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# ============================================
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# SECONDARY
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# ============================================
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git+https://github.com/facebookresearch/segment-anything-2.git
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# ============================================
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# TERTIARY
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# ============================================
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rembg==2.0.53
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onnxruntime-gpu==1.16.3
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# ============================================
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# Supporting Libraries
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# ============================================
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# Transformers & HuggingFace
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transformers
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accelerate
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huggingface-hub
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safetensors
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tokenizers
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# Computer Vision
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timm
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albumentations
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ultralytics
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supervision
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# Image Processing
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scipy
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scikit-image
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matplotlib
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imageio
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imageio-ffmpeg
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# Video Processing
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moviepy
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av
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decord==0.6.0
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# ML Libraries
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xgboost
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lightgbm
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scikit-learn
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# Data Processing
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pandas
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pyarrow
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# Progress & UI
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tqdm
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rich
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# Web & Downloads
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requests
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httpx
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aiohttp
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# Memory Management
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memory-profiler
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pympler
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objgraph
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# Parallel Processing
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joblib
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threadpoolctl
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# Utilities
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python-dotenv
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fire
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typer
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#
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# Audio support (for videos with sound)
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librosa==0.10.1
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soundfile==0.12.1
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pydub==0.25.1
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# Advanced CV models
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open-clip-torch
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clip-interrogator
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groundingdino-py
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# Monitoring
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wandb
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tensorboard
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# ============================================
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# NOTES:
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# 1. MatAnyone provides best quality with temporal consistency
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# 2. SAM2 is video-optimized segmentation
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# 3. Rembg is fast fallback
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# 4. OpenCV is always available (comes with opencv-python)
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# 5. Models download dynamically on first use
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# 6. Total package size: ~10-15GB
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# 7. Models add: 500MB-2GB depending on selection
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# ============================================
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# ============================================
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# FIXED REQUIREMENTS - MatAnyone compatible
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# ============================================
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# Core Dependencies
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streamlit==1.32.2
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opencv-python-headless==4.8.1.78
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opencv-contrib-python==4.8.1.78
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numpy==1.26.4
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Pillow==10.2.0
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nvidia-ml-py==12.535.161
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py3nvml==0.2.7
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# NOTE: PyTorch handled in Dockerfile
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# Don't include torch/torchvision/torchaudio here
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# ============================================
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# PRIMARY: MatAnyone (with its dependencies)
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# ============================================
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git+https://github.com/pq-yang/MatAnyone.git
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# ============================================
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# SECONDARY: SAM2
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# ============================================
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git+https://github.com/facebookresearch/segment-anything-2.git
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# ============================================
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# TERTIARY: Rembg
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# ============================================
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rembg==2.0.53
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onnxruntime-gpu==1.16.3
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# ============================================
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# Supporting Libraries - NO VERSION PINNING!
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# Let pip resolve versions automatically
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# ============================================
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# Transformers & HuggingFace
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transformers
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accelerate
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huggingface-hub
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safetensors
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tokenizers
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# Computer Vision
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timm
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albumentations
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ultralytics
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supervision
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# Image Processing - NO VERSION for imageio!
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scipy
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scikit-image
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matplotlib
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imageio # NO VERSION - let MatAnyone decide!
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imageio-ffmpeg
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# Video Processing
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moviepy
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av
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# ML Libraries
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xgboost
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lightgbm
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scikit-learn
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# Data Processing
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pandas
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pyarrow
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# Progress & UI
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tqdm
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rich
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# Web & Downloads
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requests
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httpx
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aiohttp
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# Memory Management
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memory-profiler
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pympler
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objgraph
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# Parallel Processing
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joblib
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threadpoolctl
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# Utilities
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python-dotenv
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fire
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typer
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# Audio support
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librosa
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soundfile
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pydub
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# Advanced CV models
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open-clip-torch
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clip-interrogator
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+
groundingdino-py
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# Monitoring
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wandb
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tensorboard
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