This project converts a landscape video (e.g., 16:9) to a portrait format (9:16) suitable for mobile devices. It dynamically crops the video based on face detection to ensure the main subject remains centered.

• Extracts frames from the input video.
• Detects faces in each frame using DLIB.
• Determines optimal crop positions to center the largest detected face.
• Smooths crop positions to prevent jitter.
• Generates video segments based on crop positions.
• Processes video segments with FFmpeg.
• Concatenates segments and reapplies the original audio.
• Implements robust logging for easy debugging and monitoring.
• Cleans up temporary files after processing.

• Python 3.6+
• FFmpeg
• Homebrew (for macOS users)
• Python Libraries:
  • opencv-python
  • dlib
  • numpy

1. Install Dependencies:

   It's recommended to use a virtual environment.

   python3 -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install --upgrade pip
   pip install -r requirements.txt

2. Install dlib:

   brew install cmake boost
   pip install dlib

   Note: Ensure that cmake and boost are installed via Homebrew before installing dlib via pip.

1. Configure Parameters:

   Edit config.py to set your input video path and output directories.

2. Run the main script:

   python3 main.py

3. Output:

   • The final cropped video will be saved as specified in config.py (default: final_cropped_video.mp4).
   • A log file named video_analysis.log will be created in the project directory, detailing the processing steps and any issues encountered.

To Enable Debug Logging:

Modify the setup_logging function in utils.py to set the log level to DEBUG:

def setup_logging(log_file='video_analysis.log'):
    """
    Configures the logging settings.

    Args:
        log_file (str): Path to the log file.
    """
    logging.basicConfig(
        level=logging.DEBUG,  # Changed from INFO to DEBUG
        format='%(asctime)s - %(levelname)s - %(message)s',
        handlers=[
            logging.FileHandler(log_file, mode='w'),
            logging.StreamHandler()
        ]
    )
    logging.info("Logging is configured.")