Autonomous driving - car detection using the very powerful YOLO model

Detecting Cars in real time and identifying the speed of cars and tracking

Car's plate detection and car's colour detection with YOLO5 and LPRnet

This is a Multi object tracker. Mainly it was build for tracking car movement in a junction.

Detecting Cars in real time and identifying the speed of cars and tracking

"Car Detection" is trained in Keras using Tensorflow as back-end. It's taking an image as input & gives a binary decision whether a car is present in the image or not.

Simple car and pedestrian detection in video using "openCV" library 🚗 🚶

This model is very useful to detecting cars, buses, and trucks in a video.

Car-Model-Detection is a Python project that uses transfer learning with the ResNet50 model to detect the brand of cars.

Mini Projects like lane detection, face detection, car detection, pedestrian detection and segmentation using only OpenCV tools.

This repository is related to an autonomous car drive project.

Deep Learning Projects | Neural Networks | Regularization & Gradiant Descent | TensorFlow | Face Recognition | Art generation | Yolo Algorithm (Object Detection)

Car Detection for Autonomous driving using YOLO algorithm.

Detection of cars from video or live webcam using opencv python

Car detection using YOLO

Detecting Cars in a video using OpenCV and the pretrained haarcascade data set for car detection!

"Car Detection" is trained in Keras using Tensorflow as back-end. It's taking an image as input & gives a binary decision whether a car is present in the image or not.

Cars and Pedestrains Detection