53 lines
1.5 KiB
Plaintext
53 lines
1.5 KiB
Plaintext
# Raspberry Pi Compatible Requirements
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# Optimized for ARM architecture and Python 3.9-3.11
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# Core Framework
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streamlit>=1.28.0,<2.0.0
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# Computer Vision
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opencv-python>=4.8.0,<5.0.0
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opencv-contrib-python>=4.8.0,<5.0.0 # Additional OpenCV modules for face detection
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numpy>=1.24.0,<2.0.0
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# Deep Learning Models
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ultralytics>=8.0.0,<9.0.0
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torch>=2.0.0,<3.0.0
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torchvision>=0.15.0,<1.0.0
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transformers>=4.30.0,<5.0.0
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onnxruntime>=1.15.0,<2.0.0
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# Face & Pose Analysis - Raspberry Pi Compatible Options
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#
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# IMPORTANT: MediaPipe installation varies by Python version and architecture.
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# Install MediaPipe separately based on your setup:
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#
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# Option 1: Python 3.9-3.10 (try MediaPipe 0.10.8)
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# pip install mediapipe==0.10.8
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#
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# Option 2: Python 3.11+ (try MediaPipe 1.0+)
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# pip install mediapipe>=1.0.0
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#
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# Option 3: 32-bit Raspberry Pi OS
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# pip install mediapipe-rpi4
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#
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# Option 4: If MediaPipe fails, the code will automatically use OpenCV fallback
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# (No MediaPipe installation needed - just install other requirements)
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#
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# Uncomment ONE of the following if you want to specify in requirements:
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# mediapipe>=0.10.0,<0.11.0 # For Python 3.9-3.10
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# mediapipe>=1.0.0 # For Python 3.11+
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# mediapipe-rpi4 # For 32-bit Raspberry Pi OS
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# External APIs
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roboflow>=1.1.0,<2.0.0
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# Machine Learning
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scikit-learn>=1.3.0,<2.0.0
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# Utilities
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pyyaml>=6.0,<7.0
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# Additional dependencies for OpenCV face detection fallback
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# (OpenCV DNN face detector models will be downloaded automatically)
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