Popular GitHub Repositories for Csi Driver

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

An open source advanced driver assistance system (ADAS) that uses Jetson Nano as the hardware. Features: Traffic sign detection, Forward collision warning, Lane departure warning.

CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)

AI-powered key driver analysis tool that pinpoints root cause behind metrics fluctuation in one minute.

Learning human driver models from NGSIM data with imitation learning.

Driver Drowsiness Detector detects if a driver or a person is drowsy or not, using their eye movements.

Simple process for camera installation, software and hardware setup, and object detection using Yolov5 and openCV on NVIDIA Jetson Nano.

drowsiness detection

A real-time drowsiness detection system for drivers, which alerts the driver if they fall asleep due to fatigue while still driving. The computer vision algorithm used for the implementation uses a trifold approach to detect drowsiness, including the measurement of forward head tilt angle, measurement of eye aspect ratio (to detect closure of eyes) and measurement of mouth aspect ratio (to detect yawning).

This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.

PyTorch Implementation of "Driver Anomaly Detection: A Dataset and Contrastive Learning Approach", codes and pretrained models.

[TPAMI 2018] Predicting the Driver’s Focus of Attention: the DR(eye)VE Project. A deep neural network learnt to reproduce the human driver focus of attention (FoA) in a variety of real-world driving scenarios.

Ubuntu 18.04 How to install Nvidia driver + CUDA + CUDNN + build tensorflow for gpu step by step command line

A computer vision system made with the help of opencv that can automatically detect driver drowsiness in a real-time video stream and then play an alarm if the driver appears to be drowsy.

SafeDriveVision is a computer vision project aimed at enhancing road safety. This project leverages deep learning models to detect and alert in real-time the dangerous behaviors of drivers, such as using a phone while driving or showing signs of drowsiness.

Learn to create & deploy a deep learning algorithm into a production REST API microservice using Python, Keras, FastAPI, & NoSQL.

This add-on implements a speech synthesizer driver for NVDA using neural TTS models. It supports Piper

Intelligent Driver Monitoring system for Autonomous Vehicles

Eye state classification using OpenCV and DLib to estimate Percentage Eye Closure (PERCLOS) and alert a drowsy person (such as a driver).

An implementation for our paper: CsiGAN: Robust Channel State Information-based Activity Recognition with GANs (IEEE Internet of Things Journal, 2019), which is the semi-supervised Generative Adversarial Network (GAN) for Channel State Information (CSI) -based activity recognition.