vehicle-detection
There are 322 repositories under vehicle-detection topic.
ndrplz/self-driving-car
Udacity Self-Driving Car Engineer Nanodegree projects.
ahmetozlu/vehicle_counting_tensorflow
:oncoming_automobile: "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
JunshengFu/vehicle-detection
Created vehicle detection pipeline with two approaches: (1) deep neural networks (YOLO framework) and (2) support vector machines ( OpenCV + HOG).
andrewssobral/vehicle_detection_haarcascades
Vehicle Detection by Haar Cascades with OpenCV
andrewssobral/simple_vehicle_counting
Vehicle Detection, Tracking and Counting
xslittlegrass/CarND-Vehicle-Detection
Vehicle detection using YOLO in Keras runs at 21FPS
yukitsuji/3D_CNN_tensorflow
KITTI data processing and 3D CNN for Vehicle Detection
tugot17/YOLO-Object-Counting-API
The code of the Object Counting API, implemented with the YOLO algorithm and with the SORT algorithm
chenjoya/Vehicle_Detection_Recognition
This is a Matlab lesson design for vehicle detection and recognition. Using cifar-10Net to training a RCNN, and finetune AlexNet to classify. Thanks to Cars Dataset:http://ai.stanford.edu/~jkrause/cars/car_dataset.html
tomazas/opencv-lane-vehicle-track
OpenCV implementation of lane and vehicle tracking
antevis/CarND-Project5-Vehicle_Detection_and_Tracking
Vehicle Detection with Convolutional Neural Network
shreyapamecha/Speed-Estimation-of-Vehicles-with-Plate-Detection
The main objective of this project is to identify overspeed vehicles, using Deep Learning and Machine Learning Algorithms. After acquisition of series of images from the video, trucks are detected using Haar Cascade Classifier. The model for the classifier is trained using lots of positive and negative images to make an XML file. This is followed by tracking down the vehicles and estimating their speeds with the help of their respective locations, ppm (pixels per meter) and fps (frames per second). Now, the cropped images of the identified trucks are sent for License Plate detection. The CCA (Connected Component Analysis) assists in Number Plate detection and Characters Segmentation. The SVC model is trained using characters images (20X20) and to increase the accuracy, 4 cross fold validation (Machine Learning) is also done. This model aids in recognizing the segmented characters. After recognition, the calculated speed of the trucks is fed into an excel sheet along with their license plate numbers. These trucks are also assigned some IDs to generate a systematized database.
guptavasu1213/Yolo-Vehicle-Counter
This project aims to count every vehicle (motorcycle, bus, car, cycle, truck, train) detected in the input video using YOLOv3 object-detection algorithm.
windowsub0406/Vehicle-Detection-YOLO-ver
real-time Vehicle Detection( tiny YOLO ver) and HOG+SVM method
hlesmqh/WS3D
Official version of 'Weakly Supervised 3D object detection from Lidar Point Cloud'(ECCV2020)
ahmetozlu/vehicle_counting
Vehicle detection, tracking and counting by blob detection with OpenCV on c++.
ahmetozlu/vehicle_counting_hog_svm
Vehicle detection, tracking and counting by SVM is trained with HOG features using OpenCV on c++.
subodh-malgonde/vehicle-detection
Detect vehicles in a video
wsh122333/Multi-type_vehicles_flow_statistics
According to YOLOv3 and SORT algorithms, counting multi-type vehicles. Implemented by Pytorch.
jasur-2902/CarRecognition
This is one of the best vehicle recognition applications. It can determine the car's license plate number, color, model, brand and year.
Ekim-Yurtsever/DeepTL-Lane-Change-Classification
Driving risk assessment with deep learning using a monocular camera. Related paper: https://arxiv.org/abs/1906.02859
akhilesh-k/Lane-and-Vehicles-Detection
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.
xfgryujk/VehicleDetection
Detect and track vehicles in video
hayoung-kim/Perception-for-Self-driving
Perception algorithms for Self-driving car; Lane Line Finding, Vehicle Detection, Traffic Sign Classification algorithm.
sekilab/VehicleOrientationDataset
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.
Landzs/Tracking_Multiple_Objects_In_Surveillance_Cameras
Automatic detection and tracking of moving vehicles in a video from a surveillance camera
ozcanovunc/opencv-samples
Sample use cases in OpenCV 🎨
vanhaito/YOLOX-ByteTrack-Car-Counter
Car tracking and car counter implemented with YOLOX, ByteTrack and Pytorch.
VedantKhairnar/Adaptive-Traffic-Signal-Control-System
The name says everything...
hankerkuo/Vehicle-Front-Rear-Detection-for-License-Plate-Detection-Enhancement
A Network for detecting and classifying vehicle's front and rear
nikitalpopov/vedai
vedai dataset for darknet
rmcqueen/traffic-monitor
Automate traffic counting with a Raspberry Pi and Computer Vision
kuldeepbishnoi/Automatic-Emergency-Braking
Implementation of the Automatic Emergency Braking System using deep learning.
Kalebu/Real-time-Vehicle-Dection-Python
A python project that does real-time vehicle detection using a trained car-cascade Model
LdDl/odam
ODAM - Object detection and Monitoring