Anubriya/Fruit_Detection_using_YOLOv8

Fruit-Object-Detection

🍎🍌🍊 Fruit Detection using YOLOv8 A deep-learning project that detects Apples, Bananas, and Oranges using a trained YOLOv8 Object Detection model. This project includes dataset preparation, training, evaluation, visualization, Streamlit app deployment.

🚀 Project Overview

• —Trained YOLOv8n model on custom fruit dataset
• —Evaluated using:
• —Precision, Recall
• —mAP50, mAP50-95
• —Confusion Matrix
• —PR Curves
• —Built a Streamlit Web App for real-time fruit detection
• —Hosted online using Hugging Face Spaces

Features

• —Upload an image
• —Perform object detection
• —Display detected fruits with bounding boxes
• —Runs on Streamlit in Hugging Face Spaces

Tech Stack

• —YOLOv8 (Ultralytics)
• —Streamlit
• —Python
• —Hugging Face Spaces

Model

Trained for 30 epochs on custom dataset.

How to Use

1. 1.Upload an image
2. 2.Click "Detect Fruits"
3. 3.View results on screen

By Anubriya.B