There are 2 repositories under pothole-detection topic.
Easy-to-use finetuned YOLOv8 models.
Attention Aggregation Framework in PyTorch, ECCV Workshops 2020
🥇 1st place winner | Bump.IT - Pothole detection and mapping. Using data science methods of analysis, mobile phone's telemetry, computer vision, and, deployed through Azure.
Spothole Core Backend (Object Detection + Flask API) - Artificial Intelligence Powered Pothole Detection, Reporting and Management Solution
Pothole Detection || Pothole Detection using python and deep learning
Road Damage Detection Based on Unsupervised Disparity Map Segmentation (T-ITS)
Pothole detection using image processing scheme
Helping navigate through maps to prefer road-way.
Pothole Detection using Image Segmentation by using a custom dataset with over 700+ images trained on Roboflow and predicting using the latest Ultralytics YOLOv8.
The Model will detect whether the image consists of potholes or not. If the image consists of pothole then it will detect the total number of potholes in the image as well as it will assign them a level.
A mobile application made in Flutter that is capable of detecting potholes in real-time and alerting the driver to avoid any accidents caused by potholes. The app also estimates approx dimensions of the pothole to measure the severity may caused upon accident.
Road transport is the most widely used means of transportation around the world. With this high use of road transport, the safety of travellers’ becomes the prime concern for any governing authority. While some safety concerns arise from driver errors and environmental factors, most cases are a result of poor maintenance of these roads. Potholes, specifically, are one of the leading causes of road accidents throughout the world and need to be taken care of immediately, by the authorities. This paper presents a solution that makes use of civilians’ mobile sensors, along with image-based alternatives to detect potholes in real-time, using Machine Learning. The concerned authorities are then notified about the same through a web-based portal, to take the necessary action. The solution also incorporates pivoting existing complaints, location tagging and prioritization. Additionally, the solution provides a forecast of the likelihood of issues regarding potholes, constantly updating time series data of the locations.
Dataset accompanying the paper titled "Pothole detection and dimension estimation system using deep learning (YOLO) and image processing"
Pothole detection using python OpenCV on GUI based Console
Using deep learning and transfer learning techniques to differentiate plain roads and those with potholes using three different classifiers to obtain the best accuracy with the same convolutional base
This dataset could be used for automatically finding and categorizing potholes in city streets so the worst ones can be fixed faster.
Поиск выбоин на дорогах с использованием YOLOv8 Nano
Build a computer vision-based technology to process and detect the potholes present in an image.
Integrated real-time data analytics for optimized public transport, innovative road monitoring using demand prediction, and conditioning tech for sustainability, real time pothole detection either by image or video, smart parking count system for efficiency using AI/ML.
This is our idea submission for the Nvidia hack in AI hack 2022.
Spothole (Authority App) - Artificial Intelligence Powered Pothole Detection, Reporting and Management Solution
A pothole detection DL algorithm using Yolo v2 and Tensorflow
An intelligent Pothole Detection system using YOLOv4 Tiny, capable of identifying and categorizing potholes . The severity level of each pothole (Low, Medium, High) is assessed based on its area in the frame. This system provides a valuable tool for monitoring road conditions and prioritizing maintenance efforts.
Pothole Detection using Faster-RCNN and YOLO v3
Pothole Detection Using Transfer Learning Models: A Comparative Study
This is a pothole detection detection system created using Image Classification by Convolutional Neural Networks.
The pilot vehicle rounds the city daily and sends the pothole coordinates to the cloud. The app will display the pothole and if the user is near the pothole, the user will be alerted
A computer Vision project for avoiding potholes on road.
CS512-Computer vision assignments and project
1200-Videos-Potholed-Road-Collection-Data
Backend code for a real-time pothole detection system sending location data to Firebase's Realtime Database.