Objective: To classify food images in different food categories using pre-trained YOLO11 model
An application for tracking human posture
CandyMeter is a computer vision project that uses YOLO to detect candies and estimate calorie intake in real time. Supporting 11 classes, it works across images, videos, and live camera feeds, overlaying bounding boxes, confidence scores, counts, and calorie values. It showcases deep learning for nutrition tracking & food recognition app
📚This repository includes a script for testing segmentation models and calculating fill ratios from segmentation masks
This study is based on computer vision and deep learning technologies, and has developed a comprehensive intelligent detection system for container surface damage, achieving multi-level detection tasks from determining the presence of damage to precise localization and classification.
AMBATRON (Automated Monitoring Bot for Anomalies) is a surveillance robot that uses an ESP32 microcontroller and computer vision to detect visual anomalies. It moves when unusual or suspicious objects are detected through a camera using a custom-trained image recognition model.
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