YOLO Real-time Object Detection with Text-to-Speech

Overview

This Python project utilizes the YOLO (You Only Look Once) real-time object detection model to identify objects in a video feed from a camera. Detected object labels are then converted into speech using the Text-to-Speech (TTS) library pyttsx3.

Tech Stack

• OpenCV: Library for computer vision and video processing.
• PyTorch: Deep learning framework (required by YOLO).
• Ultralytics YOLO: YOLO implementation for PyTorch.
• pyttsx3: Python library for Text-to-Speech.

Installation

Ensure you have the required libraries installed:

pip install opencv-python
pip install pyttsx3
pip install git+https://github.com/ultralytics/yolov5.git

Note

Ensure that the camera is connected and functional. Adjust the YOLO confidence threshold (conf) as needed for your use case. You may need to install additional dependencies based on your system configuration.