This project focuses on developing a YOLO (You Only Look Once) object detection model capable of detecting and identifying drug names from images of pharmaceutical packaging.
This project is an improvement on a previous project built for COMP 351 at USD. The original project used a CNN (Convolutional Neural Network) for image classification, but this version uses YOLO for object detection, which is better suited for locating and identifying drug names with bounding boxes in pharmaceutical packaging images.
- YOLO Object Detection: Uses YOLO architecture for real-time drug name detection
- Bounding Box Localization: Accurately locates drug names within images
- Pharmaceutical Packaging: Trained on medicine boxes, bottles, and blister packs
- Dataset: Uses the Drug Name Detection Dataset from Kaggle (~1,823 annotated images)
- Pharmacy inventory management
- Counterfeit drug detection
- Automated label verification for hospitals and supply chains
- Python 3.12 (recommended)
- YOLO framework (Ultralytics YOLO recommended)
- See notebook for full dependency list