🦷 Dental Disease Detection Using YOLOv8/YOLOv10 and Flask

A deep learning-powered web application for real-time dental disease prediction from X-ray images. This tool utilizes cutting-edge YOLOv8n/m and YOLOv10s object detection models to classify six dental conditions and assist clinicians in diagnosing oral health issues efficiently.

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🚀 Features

• ⚙️ YOLO-Based Detection: Utilizes Ultralytics' YOLOv8 and YOLOv10 models to detect and classify:

  • Caries
  • Infection
  • Impaction
  • Fractures
  • Root canal issues
  • Missing teeth

• 🎯 Model Performance:

  • Achieved 92% mAP@0.5
  • Recall: 0.8194
  • Trained over 250 epochs on a custom-labeled dental X-ray dataset

• 🌐 Web Interface:

  • Built using Vite + React for a fast and responsive front end
  • Backend powered by Flask to serve predictions in real time
  • Upload dental radiographs and receive immediate annotated results

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🛠️ Tech Stack

Layer	Technologies Used
Frontend	React (Vite), Tailwind CSS
Backend	Python, Flask
Model	YOLOv8n, YOLOv8m, YOLOv10s (Ultralytics)
Dataset	Custom-labeled dental X-ray images

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