The Automated Attention Tracking and Reporting system is a sleek AI-driven dashboard that provides real-time monitoring and reporting of distraction levels during classes, meetings, or lectures. Utilizing advanced computer vision techniques to help educators and facilitators enhance focus and attention during sessions.

An app to count and track pedestrians, bike riders, e-scooter riders, and people in wheelchairs.

This project detects the car license plate through a free Roboflow API, submits the detected car license plate image to a battery of filters and obtains the car license plate number using paddleOcr

From dataset https://universe.roboflow.com/drone-detection-pexej/drone-detection-data-set-yolov7/dataset/1# a model is obtained, based on ML (SVR), with that custom dataset, to indicate drones detection

From dataset https://universe.roboflow.com/roboflow-100/bone-fracture-7fylg a model is obtained, based on ML (SVR), with that custom dataset, to indicate fractures in x-rays.

This work is an extension of the project https://github.com/ablanco1950/LicensePlate_RoboflowAPI_Filters_PaddleOCR adding the possibility to detect the speed

From dataset https://universe.roboflow.com/test-svk7h/brain-tumors-detection/dataset/2 a model is obtained, based on yolov10 to indicate tumors in images of brains.

From dataset https://universe.roboflow.com/roboflow-100/bone-fracture-7fylg a model is obtained, based on yolov10, with that custom dataset, to indicate fractures in x-rays. The project uses 5 cascade models, if one does not detect fracture it is passed to another