https://github.com/gold-roger33/mini-project-yolo-object-detection
Object Detection System using Raspberry Pi and python
https://github.com/gold-roger33/mini-project-yolo-object-detection
python raspberry-pi ultralytics
Last synced: about 2 months ago
JSON representation
Object Detection System using Raspberry Pi and python
- Host: GitHub
- URL: https://github.com/gold-roger33/mini-project-yolo-object-detection
- Owner: gold-roger33
- Created: 2024-03-19T17:26:04.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-12T12:59:42.000Z (about 2 years ago)
- Last Synced: 2025-02-27T03:26:08.797Z (over 1 year ago)
- Topics: python, raspberry-pi, ultralytics
- Language: Python
- Homepage:
- Size: 17.9 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Object Detection System for Visually Impaired: Raspberry Pi & Python(Mini Project)
This repository is the code for my mini project that demonstrates real-time object detection using the YOLO (You Only Look Once) model in Raspberry Pi pi 4B.
The project is designed to assist the visually impaired by detecting and announcing objects in their surroundings.
## Features
- Real-time object detection using YOLO model
- Video input from the camera module/webcam
- Detection of various classes of objects
- Announcement of detected objects and their positions using text-to-speech engine
## Requirements
- Python 3.12
- ultralytics library
- pyttsx3 library
- Pre-trained YOLO model (yolov8n.pt)
- camera module (you can use web camera)
- Raspberry Pi (You can also run on PC)
## Usage
1. Clone the repository:
```bash
git clone https://github.com/gold-roger33/mini-project-yolo-object-detection.git
```
2. Install the required libraries:
```bash
pip install ultralytics pyttsx3
```
3. Run the main script:
```bash
cd final code
python livecam.py
```
4. Point the camera module towards the surroundings and listen to the announcements of detected objects.
## Additionals
There is a test folder which i used to test some features like detecting objects from video
## credits
- Ultralytics YOLO: [Documentation](https://docs.ultralytics.com/quickstart/)