基于深度学习的驾驶员分心驾驶行为（疲劳+危险行为）预警系统使用YOLOv5+Deepsort实现驾驶员的危险驾驶行为的预警监测

Experimenting with sort different classical tracking algorithms for real time multiple object tracking (MOT)

Vehicle Speed Check

Face recognition using dlib and kNN classification (ROS compatible)

🏋️Barbell path tracker based on OpenCV and Dlib

Vehicle counter using python opencv and dlib

This project aims to do virtual makeup on the face of a person using dib and keras libraries.

dlib correlation tracker bindings to run in the browser, using emscripten

VROID unity application with face detection functionalities

Multi-object tracking using pre-trained MobileNet SSD caffe model with dlib and openCV

The AI Face Recognition System is a cutting-edge project that utilizes artificial intelligence to transform face recognition technology. Equipped with advanced algorithms and neural networks, this system delivers unparalleled accuracy and speed in identifying individuals based on their distinctive facial features

Python simple object tracking example with OpenCV and dlib

Centroid tracking algo used for directions determination and maintaining counts

Built a tool that can track a student's attentiveness in an online class and can alert teacher if student isn't attentive using Computer Vision.

Detect, track and recognize faces. Store them for further analysis (for Raspberry Pi).

Face Recognition project based on MTCNN, Insightface (MXNET) and Keras.

This repository comprises a computer vision algorithm designed for counting the fingers displayed by the user's left hand in real-time. Additionally, it features an interactive game in which the user is invited to accurately replicate the number prompted by the system.

OpenCV prototype linked integrate frameworks using HAAR Classification and DLib & CLM Face Detection models composed by a collection of miscellaneous Machine Learning, Computer Vision, Image Processing, and Linear Algebra algorithms.