Face Spotter

The Face Spotter application is a Python-based tool designed to detect, track, and manage users via facial recognition. It allows you to register users, track their activity in real-time using a camera, generate reports, and manage user details (e.g., rename or update images).

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Table of Contents

1. Features
2. Installation
3. Usage
4. File Structure
5. Troubleshooting
6. Contributing
7. License

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Features

• User Registration: Register new users manually by providing a name and uploading an image.
• Real-Time Tracking: Detect and track registered users in real-time using a webcam.
• Automatic Unknown User Registration: Automatically registers unknown faces with random names.
• Activity Reporting: Generate detailed reports of user activity, including start time, end time, and duration.
• User Management:
  • Rename users.
  • Update user profile images.
  • Delete users.
• Customizable Timeout: Configure the timeout period for closing user tracking intervals.
• Filterable Reports: View reports filtered by specific users or all users.

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Installation

Prerequisites

• Python 3.8 or higher
• A webcam or camera connected to your system
• Supported operating systems: macOS, Windows, Linux

Dependencies

Install the required Python libraries using pip:

pip install opencv-python face-recognition numpy pillow

For macOS users, you may need to install OpenCV with AVFoundation support:

pip install opencv-python-headless

Setup

1. Clone the repository or download the source code.
2. Ensure the following directories exist in the project folder:
   • encodings/ (for storing user encodings)
   • images/ (for storing user profile images)
3. Place a custom icon file (icon.png) in the root directory if you want to use a custom application icon.

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Usage

Running the Application

Run the application using the following command:

python app.py

Main Features

1. Register a New User:

   • Enter a name in the input field.
   • Click "Register User" and select an image file containing the user's face.

2. Start Tracking:

   • Click "Start Tracking" to begin detecting and tracking users in real-time.
   • Detected users will be displayed on the camera feed with their names and active durations.

3. Manage Users:

   • Click "Manage Users" to view, rename, update images, or delete users.

4. View Reports:

   • Click "View Report" to see a detailed report of user activity.
   • Use the dropdown menu to filter reports by a specific user or view all users.

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File Structure

user-tracker/
├── app.py                  # Main application script
├── encodings/              # Directory for storing user encodings (.npy files)
├── images/                 # Directory for storing user profile images (.jpg files)
├── users.csv               # CSV file for storing user data (name, encoding path, image path)
├── user_tracking_report.csv # Generated report file for user activity
├── icon.png                # Custom application icon (optional)
└── README.md               # Documentation file

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Troubleshooting

Common Issues and Solutions

1. Camera Not Working:

   • Ensure your camera is connected and working properly.
   • On macOS, try installing OpenCV with AVFoundation support:

     pip install opencv-python-headless

2. Indentation Errors:

   • Ensure all code blocks are properly indented (Python uses 4 spaces per indentation level).

3. Missing Dependencies:

   • Install missing dependencies using pip install <package-name>.

4. Face Not Detected:

   • Ensure the uploaded image has a clear, visible face.
   • Adjust lighting conditions when using the camera.

5. Old Reports Not Updated After Renaming a User:

   • Ensure the update_username function is correctly implemented to update both the users.csv and user_tracking_report.csv files.

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Contributing

We welcome contributions to improve this project! To contribute:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Submit a pull request with a detailed description of your changes.