concrete surface crack detection using yolov5 model Object Detection Dataset and Pre-Trained Model by vijayalakshmi

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Here are a few use cases for this project:

Infrastructure Inspections and Maintenance: Structural engineers and maintenance teams could use this model to detect cracks in bridges, roads, and buildings, helping to prioritize maintenance tasks and potentially prevent structural failures.
Safety Inspections in Construction Industry: Firms could integrate the model into an app/software to assist site inspectors in assessing concrete quality in new construction projects, ensuring adherence to safety standards.
Drone-based Inspection Services: The model could be incorporated into the software of drones used for industrial or commercial inspections. This would make it easy to survey large or hard-to-reach areas for concrete cracks, such as dams, skyscrapers or tunnels.
Automated Home Inspection Services: Businesses providing home buyer's pre-purchase inspections could use it to reliably detect any structural issues in the properties, giving their customers detailed and accurate information about the property's condition.
Disaster Damage Assessment: The model could be used by rescue teams or insurance adjusters to assess damage after disasters such as earthquakes or storms, helping them to quickly identify structures that might be in danger of collapsing.

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.

Cite This Project

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

@misc{
                            concrete-surface-crack-detection-using-yolov5-model_dataset,
                            title = { concrete surface crack detection using yolov5 model Dataset },
                            type = { Open Source Dataset },
                            author = { vijayalakshmi },
                            howpublished = { \url{ https://universe.roboflow.com/vijayalakshmi-2yshx/concrete-surface-crack-detection-using-yolov5-model } },
                            url = { https://universe.roboflow.com/vijayalakshmi-2yshx/concrete-surface-crack-detection-using-yolov5-model },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-05-12 },
                            }