# Raspberry Pi Compatible Requirements
# Optimized for ARM architecture and Python 3.9-3.11

# Core Framework
streamlit>=1.28.0,<2.0.0

# Computer Vision
opencv-python>=4.8.0,<5.0.0
opencv-contrib-python>=4.8.0,<5.0.0  # Additional OpenCV modules for face detection
numpy>=1.24.0,<2.0.0

# Deep Learning Models
ultralytics>=8.0.0,<9.0.0
torch>=2.0.0,<3.0.0
torchvision>=0.15.0,<1.0.0
transformers>=4.30.0,<5.0.0
onnxruntime>=1.15.0,<2.0.0

# Face & Pose Analysis - Raspberry Pi Compatible Options
# 
# IMPORTANT: MediaPipe installation varies by Python version and architecture.
# Install MediaPipe separately based on your setup:
#
# Option 1: Python 3.9-3.10 (try MediaPipe 0.10.8)
#   pip install mediapipe==0.10.8
#
# Option 2: Python 3.11+ (try MediaPipe 1.0+)
#   pip install mediapipe>=1.0.0
#
# Option 3: 32-bit Raspberry Pi OS
#   pip install mediapipe-rpi4
#
# Option 4: If MediaPipe fails, the code will automatically use OpenCV fallback
#   (No MediaPipe installation needed - just install other requirements)
#
# Uncomment ONE of the following if you want to specify in requirements:
# mediapipe>=0.10.0,<0.11.0  # For Python 3.9-3.10
# mediapipe>=1.0.0           # For Python 3.11+
# mediapipe-rpi4             # For 32-bit Raspberry Pi OS

# External APIs
roboflow>=1.1.0,<2.0.0

# Machine Learning
scikit-learn>=1.3.0,<2.0.0

# Utilities
pyyaml>=6.0,<7.0

# Additional dependencies for OpenCV face detection fallback
# (OpenCV DNN face detector models will be downloaded automatically)