#Vehicle-detection
Showing 9 of 9 repositories tagged #vehicle-detection, ranked by stars
Udacity Self-Driving Car Engineer Nanodegree projects.
:oncoming_automobile: "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
Detect vehicles in a video
The vehicle orientation dataset is a large-scale dataset containing more than one million annotations for vehicle detection with simultaneous orientation classification using a standard object detection network.
Driving risk assessment with deep learning using a monocular camera. Related paper: https://arxiv.org/abs/1906.02859
This repository contains works on a computer vision software pipeline built on top of Python to identify Lanes and vehicles in a video. This project is not part of Udacity SDCND but is based on other free courses and challanges provided by Udacity. It uses Computer vision and Deep Learrning Techniques. Few pipelines have been tried on SeDriCa, IIT Bombay.
We developed a system that leverages on YOLO Machine Learning Model for managing the traffic flow based on the vehicle density.
ODAM - Object detection and Monitoring
🤖 This repository houses a collection of image classification models for various purposes, including vehicle, object, animal, and flower classification. Each classifier is built using deep learning techniques and pre-trained models to accurately identify and categorize images based on their respective classes. Also includes a sample Flask backend!