Defect_Detection Object Detection Dataset and Pre-Trained Model by FYP

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Explore Dataset

Here are a few use cases for this project:

Manufacturing Quality Control: Industries can use the Defect_Detection model to spot and categorize defects during the production process, ensuring that only high-quality products reach the market. This can be especially useful in automotive, aviation, and machinery manufacturing sectors where component integrity is critical.
Infrastructure Maintenance: Engineers can use the model to identify infrastructure damages such as corrosion, cracks, and pits, etc., on bridges, roads, and buildings. This can help in structuring preventative maintenance programs and assuring safety.
Oil and Gas Industry Inspection: The model can be applied to detect defects in pipelines, tanks, and other critical infrastructure where corrosion, cracks, or pits can lead to serious accidents if unnoticed.
Antique Restoration: Professionals working in art and antique restoration can utilize the model to find defects such as cracks, scratches, or pits in artifacts. This gives them insights about the degree and type of restoration needed.
Automotive Repair: Auto repair shops can harness the power of Defect_Detection to identify issues with car parts. Damage like corrosion, crack, grinding marks can be detected early, leading to timely repair and prevention of further damage.

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.

Cite This Project

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

@misc{
                            defect_detection-geufo_dataset,
                            title = { Defect_Detection Dataset },
                            type = { Open Source Dataset },
                            author = { FYP },
                            howpublished = { \url{ https://universe.roboflow.com/fyp-spp6k/defect_detection-geufo } },
                            url = { https://universe.roboflow.com/fyp-spp6k/defect_detection-geufo },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { jan },
                            note = { visited on 2024-04-25 },
                            }