DanialSoleimany/YOLOv12-Tooth-Cavity-Detection
A deep learning project for detecting and classifying teeth as normal or cavity using YOLOv12m. The model is integrated into a web application for real-time dental screening. Designed to enhance early diagnosis accessibility, with future improvements planned for dataset expansion, annotation quality, and robustness to real-world conditions.
This web application helps dental professionals quickly screen dental images for cavities. You upload an X-ray or dental photograph, and the system identifies and highlights potential cavities in red and healthy teeth in green, along with confidence scores. It's designed for dentists, dental hygienists, or dental assistants seeking an accessible tool for early diagnostic support.
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Use this if you need a rapid, visual assessment of dental images for cavity detection without installing complex software or saving files.
Not ideal if you require a certified medical diagnostic tool or need to process a very high volume of images for research purposes.
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Jupyter Notebook
License
MIT
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Last pushed
Aug 15, 2025
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