Obstacle detection Object Detection Dataset and Pre-Trained Model by visually impaired obstacle detection

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Explore Dataset

Here are a few use cases for this project:

Autonomous Vehicle Navigation: This model can be used as a part of autonomous vehicle systems for the detection and avoidance of obstacles while navigating through streets. It can assist the self-driving vehicle to classify different obstacles such as a humans, dogs, cars, motorcycles, bicycles, trams, buses, trees, traffic signs, electric poles, and even uncovered manholes.
Security Surveillance: It can be implemented in security cameras for identifying possible obstructions or threats, including unauthorized persons, suspicious vehicles, or uncovered manholes.
Smart Cities Infrastructure Planning: Local municipality or city planning departments can use the model to monitor and maintain urban infrastructure such as traffic signs, electric poles or identifying potential public safety hazards like uncovered manholes.
Assisting Visually Impaired People: The model can be incorporated into assistive technology for visually impaired people. By detecting obstacles in their path (cars, trees, uncovered manholes, etc.), the model could help guide them safely through urban spaces.
Drones and Robotic Delivery Systems: For airborne drones or ground-based robotic delivery systems, identifying and avoiding obstacles is crucial. The model could provide real-time information about potential obstructions, ensuring safe and efficient delivery of packages.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

YOLOv5

This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, state-of-the-art real-time object detection model.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            obstacle-detection-yeuzf_dataset,
                            title = { Obstacle detection Dataset },
                            type = { Open Source Dataset },
                            author = { visually impaired obstacle detection },
                            howpublished = { \url{ https://universe.roboflow.com/visually-impaired-obstacle-detection-uxdze/obstacle-detection-yeuzf } },
                            url = { https://universe.roboflow.com/visually-impaired-obstacle-detection-uxdze/obstacle-detection-yeuzf },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-04-28 },
                            }