Fish Detection System

Overview

A real-time fish species detection application using YOLO (You Only Look Once) computer vision model. Detects and identifies 13 different fish species with bounding boxes, confidence scores, and detailed species information including diet, lifespan, and estimated weight.

A comprehensive computer vision application that uses Ultralytics YOLO model for real-time fish species detection. The system consists of a FastAPI backend that processes uploaded images and returns annotated results with bounding boxes, confidence scores, and detailed metadata. The React frontend provides an intuitive interface for uploading images and displaying detection results. The application can identify 13 different fish species including AngelFish, BlueTang, ClownFish, GoldFish, and more. Each detection includes species-specific information such as diet preferences, average lifespan, and estimated weight, making it useful for marine biologists, aquarium enthusiasts, and educational purposes.

Key Features

• Real-time fish species detection using YOLO
• Detection of 13 different fish species
• Annotated images with bounding boxes and labels
• Confidence scores for each detection
• Detailed species information (diet, lifespan, weight)
• RESTful API with FastAPI backend
• Modern React frontend with Vite
• Image upload and processing pipeline
• Base64 encoded annotated image responses
• CORS-enabled for frontend-backend communication

Technologies Used