Object Detection with Audio Feedback

Overview

This project is an object detection system with audio feedback. It uses a YOLOv5 model to detect objects in real-time via a webcam, providing spoken alerts about detected objects and their positions. The system also includes a simple GUI for ease of use.

Features

• Real-time Object Detection: Uses YOLOv5 to detect objects in a webcam feed.
• Audio Feedback: Converts detected object information into speech using pyttsx3.
• GUI Interface: Built with Tkinter for easy interaction.
• Text Output: Saves detected objects with timestamps and directions in a detected_objects.txt file.
• Persistent Object Tracking: Alerts users about objects that remain in the frame for a prolonged period.

Installation

Prerequisites

Ensure you have Python installed (preferably 3.8+). Then install the required dependencies:

pip install torch torchvision torchaudio
pip install opencv-python
pip install pyttsx3
pip install pillow

Usage

Running the Object Detection System

1. Run the GUI interface:

   python gui_interface.py

2. Click the Detect button to start object detection.
3. Detected objects will be displayed on the video feed, announced via speech, and logged in detected_objects.txt.
4. Click Quit to close the application.

Alternatively, you can run object detection without the GUI:

python object_detection_audio.py

Press q to exit the detection window.

File Structure

• gui_interface.py - The graphical interface for the object detection system.
• object_detection_audio.py - Core script for object detection and audio feedback.
• detected_objects.txt - Stores detected objects along with their timestamps and locations.
• bg.jpg - Background image for the GUI (replace with your own if needed).

Customization

• Modify the confidence threshold in object_detection_audio.py:

  model.conf = 0.50  # Adjust threshold as needed

• Change speech output frequency:

  speech_interval = 5  # Seconds between speech alerts

Future Enhancements

• Add support for additional languages in audio feedback.
• Implement object tracking across frames for more precise updates.
• Enhance the GUI with more interactive features.

License

This project is licensed under the MIT License.