Parking space detection github. Detect free parking lot available for cars. This project enables real-time detection of available parking spaces in images and videos, with support for a Streamlit web interface for easy user interaction. Github repo Result Next Parking Spot Detector Description The Parking Spot Detector is a computer vision-based application designed to identify and indicate available parking spots in a parking lot using a camera feed. copy() GitHub is where people build software. boundingRect(points) points_shifted = points. It uses a deep learning model (VGG16) to classify individual parking spots as empty or occupied and serves the results through a dynamic web interface. parking-spots parking-space parking-slot-detection parking-lot-detection Updated on Apr 23, 2024 Similar techniques can be used to address the problem of parking space detection. Traditional object detection approaches, such as YOLOv8, provide fast and accurate vehicle detection across parking lots but can struggle with borderline cases, such as partially visible vehicles, small vehicles (e. Contribute to olgarose/ParkingLot development by creating an account on GitHub. It displays the video with marked Object Detection: The neural network receives the video stream and performs detection, looking specifically for the car class. ParkingSpace is a research project for real-time parking space detection using YOLOv11 and RTSP cameras. It provides real-time updates on space availability, aiding both administrators and users. Then use this coordinates . This paper simply reports the design and implementation of an SPS and does not evaluate the system performance. We’re on a journey to advance and democratize artificial intelligence through open source and open science. Starting from setting up the camera and the required network, to adjusting the program for your area. Due to occlusions (coming due to the presence of mirror in the middle of camera and parking lot which slightly reflects nearby people passing through), low resolution of video and This project is a complete, end-to-end solution for real-time parking space detection and monitoring. Extracting the parking lot coordinates form the image by car_park_coordinate_generator. Objective Capture real time image and detect filled parking locations in the parking lot using image processing. With the problems of ever increasing urban traffic congestion and the ever increasing shortage of space, the parking lots need to be well-equipped with parking space detection. It is achieved by wireless sensor in every parking space, which can detect the presence of a car in the space and note the arrival/exit time of a vehicle. By leveraging advanced image recognition techniques, the model is trained and test It offers features such as real-time detection of car parking slot occupancy, ease of use, and well-documented code. The main goal of this project is to detect and monitor car parking spaces. OpenCV is an extensive open source library (available in python, Java, and C++) that’s used for image analysis and is pretty neat. load(stream) parking_contours = [] parking_bounding_rects = [] parking_mask = [] parking_data_motion = [] if parking_data != None: for park in parking_data: points = np. In the United States alone the estimated damages for time wasted finding a parking space is billions of dollars and that is without including gas costs or air pollution. mp4) to detect the occupancy of parking spaces. Roi Poranne. In this work Jun 14, 2024 · Create a robust parking space detection system with PyTorch & Super Gradients. Park-smart is a parking solution that uses OpenCV computer vision library to detect full vs empty spots and provide that information on a row by row basis to solve the issue of motorists circling around a parking lot looking for a spot. It consists of two main parts: main. Automatic parking space detection can not only facilitate the process of looking for an parking_data = yaml. The Parking Detection System is an application designed to monitor parking spaces in real-time using a YOLOv8 object detection model. The provided dataset includes labeled images of parking lots captured Parking Space Detection Goal The goal is to determine which parking spaces are empty and which ones are occupied from a birds-eye view. Controls the parking barrier using a servo motor, based on vehicle detection by sensors. Developed under the supervision of Prof. Automated Parking Vacancy Spot Detection Overview This project utilizes computer vision and image processing techniques to detect available parking spots in a parking lot. 📌 Features Train & Validate YOLOv8 on a custom parking dataset - GitHub - ahv1365/Adaptive-Parking-Space-Detection: Identifying the vehicles and finding whether they enter in the pre-adjusted bounding boxes in every frame passing through the model is the purpose of this repository . Low-cost cameras are mounted throughout garages and mapped to locations of available parking spaces. g. Clone the repository. Uncomment the command below if needed. I leverage Tensorflow (Keras), OpenCV, and SVC to predict real-time parking spot availability. It is a popular open-source computer vision library that provides tools for image and video processing. A computer vision-based system to detect and classify parking spaces as occupied or free using video/image input. * 9. papers and codes about parking slot detection. This dataset is the largest in this field, comprising 12165 surround-view images collected from typical indoor and outdoor parking sites. Occupied/vacant status: Each parking space is marked as either occupied or vacant. Code readily runnable in google colab. May 25, 2025 · AI-powered parking space detection using YOLOv8 and OpenCV. Contribute to visualbuffer/parkingslot development by creating an account on GitHub. As a result, we will use a frame from a video of a This project utilizes the custom object detection model to monitor parking spaces in a video feed. Real time tracking of the moving vehicles in the space. Count and display the number of available parking slots in parking lot. Parking Space Detection in OpenCV. Maintaining empty parking spot count using YOLO real-time vehicle detection. Contribute to lymhust/awesome-parking-slot-detection development by creating an account on GitHub. Updates parking space availability and history based on the recognition results. To begin, a parking space detection system must identify available parking spaces. To do this, we will be using two codes: define parking spaces for cars and use YOLOv8 to detect car Parking Spot Detection Install package To use the geoai-py package, ensure it is installed in your environment. This system captures video input from a camera, detects parked cars, and provides information about the availability of parking lots. For each image, the marking points and parking slots are carefully labeled. Contribute to TheODDYSEY/Parking-OpenCv development by creating an account on GitHub. Apr 23, 2024 · Parking issues are common throughout the entire world. GitHub - Morekunall/parking-management-system: This Parking Management System is a streamlined platform connecting administrators and drivers. , motorcycles), and poor lighting conditions. The application layer can quickly pass the parking information over the Internet, and use the advantages of a web service to gather all the scattered parking information for the convenience of those who want to find a parking space. Contribute to emmm-2333/Parking-Space development by creating an account on GitHub. * 8. Designed to streamline parking management, our system offers real-time monitoring of parking spaces, enabling efficient utilization of parking facilities. Parking space occupancy detection is a critical component in the development of intelligent parking management systems. The application uses YOLO V8, a state-of-the-art object detection model, to classify parking spaces as either occupied or empty, offering real-world benefits in smart parking systems, traffic management, and resource optimization. Contribute to Chando0185/car_parking_detection_space_count development by creating an account on GitHub. This project is an AI-driven car parking monitoring system that uses YOLO (You Only Look Once) object detection and OpenCV to detect occupied and free parking spaces in real-time. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects. Contribute to sainimohit23/parking-space-detection-system development by creating an account on GitHub. This project find outs the count of empty and occioped parking spaces in a car-parking-lot using through digital image processing techniques form opencv. 🚗 Parking Segmentation System A real-time parking space detection and monitoring system using computer vision and machine learning. GitHub is where people build software. 0 Download Citation | On Oct 24, 2025, Huifang Kong and others published Parking Space Detection Based on EfficientNet-B0 and Graph Attention Network | Find, read and cite all the research you need GitHub is where people build software. We hope you find this project useful and enjoy exploring its capabilities! This project utilizes Python and computer vision techniques to detect available and occupied parking spaces using a camera feed. Overview ParkIT is designed to help you monitor parking spaces through IP cameras, detect occupied/vacant spots, and provide real-time parking occupancy analysis. The application provides a complete solution for parking management with an intuitive interface and powerful AI-driven vehicle detection capabilities. The application can process video from Vehicle Parking Detection-YOLOv8 An AI-powered parking space detection system built using Ultralytics YOLOv8. There are a number approaches for doing this, such as detecting parking places by finding the parking lines in a spot using edge detectors provided by OpenCV. DeepParking is an open-source solution for detecting vacant parking spots in indoor parking garages, and delivering real-time notifications to nearby drivers. OpenCV calculates the center of mass for these objects and checks if they fall inside the operator-defined parking zone polygons (ROIs). - neelkhot7/parking-space-detection Parking occupancy detection The key to active parking lot management is the reliable detection of available parking spaces. Parking Space Monitoring System using OpenCV 🚗. Video begins with the contours of Parking Slots overlayed the video parking-spots parking-space parking-slot-detection parking-lot-detection Updated on Apr 23, 2024 Learn how to detect parking spots in real-time using YOLO (You Only Look Once) algorithm! In this video, we'll explore a simple and efficient approach to par Automated parking occupancy detection. Contribute to anil2k/smart-car-parking-yolov5 development by creating an account on GitHub. 🚘 DeepParking Find the closest vacant parking spot, every time. In this tutorial, I will show you how to build a simple parking space detection system using deep learning. This project is part of an AICTE-assigned task, demonstrating practical application of image processing and vehicle detection techniques. * * Note: Which can be very timeconsuming for a huge parking space. Provides a web interface that refreshes periodically to display updated information. Intersection Analysis: The AI returns bounding box coordinates. * 7. Second, to facilitate the study of vision-based parking-slot detection, a large-scale labeled dataset is established. The car parking space detection project using YOLO is a computer vision system designed to detect the availability of parking spaces in a parking lot in real-time. Open File Parking Lot Detection Execute the main. Features Real-time parking space detection: The system processes video input in real-time and provides instant updates on parking space availability. Identifies empty or occupied spots from images or video, supports interactive region selection, real-time detection, and auto-generated a Parking Space Detection in OpenCV For a fun weekend project, I decided to play around with the OpenCV (Open Source Computer Vision) library in python. py by command python main. - yohmori/Parking-Space-Detection An object detection model may not be the best option… The approach of training an object detection model is alright, however in this case it might not be the best thing to do. Note that to reach the best results, you will also have to train the system with your own data set and learn how to choose the most effective regions. Utilizing image classification models, it distinguishes between occupied and vacant spots, updating counts dynamically based on video data. The Car Parking Space Detection project is a practical application of computer vision and image processing techniques designed to simplify the management and monitoring of parking spaces. This project implements a parking space detection system using computer vision. This project aims to simplify the process of finding parking spaces and enhance parking lot management. Admins list available spaces while users book spots on an hourly basis, ensuring a fast, digital experience. It identifies vehicles in the video and overlays polygons representing parking spaces on the frame Parking Space Detection using Flask and OpenCV is a web application that detects and counts free and occupied parking spaces in real time using a pre-trained CNN model. 🅿️ Parking Spot Detection System 📝 Overview This project is a machine learning and computer vision solution designed to detect and report available parking spots in real-time. This project develops a Convolutional Neural Network (CNN) model to automate the detection of free parking spaces. array(park['points']) rect = cv2. Contribute to V-prajit/GrowthFactor-Parksight-Hacklytics-2026 development by creating an account on GitHub. It identifies available parking spaces in urban environments, including areas without pre-defined spots. py Parking image will be shown Mark the contours by clicking 4 corners for each spot they want tracked Presses ‘q’ when all desired spots are marked. The system employs both deep learning-based object detection and classical computer vision techniques to ensure robustness and accuracy across various environmental conditions. py: This Python script reads the saved parking space coordinates and processes a video feed (carPark. py script. Utilizing video feed from parking lots, the system employs advanced algorithms to monitor and identify the occupancy status of each parking space. This system can be useful in car park management systems or smart city applications, where real-time information about parking spaces are provided to users to help them find parking spots quickly and easily. Current Production Version: 3. In this section, you will learn how to setup the system locally. Manage parking, reduce congestion & integrate with smart cities. In this post, I will be using the newer version of YOLO to detect available parking spaces for cars. With the increasing number of vehicles on the road, parking spaces have become scarce resources in urban areas, and it can be challenging to find available spots, especially for people with disabilities. cxqmz, fbmf, xnlzju, 2mfvh, ugn7, puv8, subcgj, x7gmsm, 0ljvz, bwzj,