requirements.txt

# Core Packages
torch==1.9.0                  # For deep learning model implementation (PyTorch)
torchvision==0.10.0           # For image transformations and pretrained models

# Data Processing and Preprocessing
numpy==1.21.0                 # Array processing and mathematical operations
opencv-python-headless==4.5.3 # For image processing, headless version for server environments
pandas==1.3.2                 # Data handling and manipulation
scikit-learn==0.24.2          # Machine learning utilities, metrics, and preprocessing

# Data Augmentation
albumentations==1.1.0         # Image augmentation library for complex data augmentations
Pillow==8.2.0                 # Image processing library for handling different image formats

# Logging and Experiment Tracking
tqdm==4.62.2                  # Progress bar for tracking loops in training and data loading
tensorboard==2.5.0            # Logging and visualization of training metrics

# Visualization
matplotlib==3.4.3             # Plotting library for visualizing training metrics and results
seaborn==0.11.2               # Statistical data visualization (used for advanced plotting)
plotly==5.3.1                 # Interactive visualization for data exploration and advanced plots

# Configuration Management
PyYAML==5.4.1                 # Reading and writing YAML configuration files

# Web Requests (for Dataset Downloading)
requests==2.26.0              # HTTP library for making requests to download datasets

# Optional: Error Reporting and Monitoring
sentry-sdk==1.3.1             # Error tracking and monitoring for deep learning experiments

# System Utilities
psutil==5.8.0                 # System and process utilities for tracking CPU and memory usage

# Testing and Debugging
pytest==6.2.5                 # Testing framework for unit tests
pytest-cov==2.12.1            # Code coverage plugin for pytest