Welding Defect - Object Detection

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Welding Defect - Object Detection

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Welding Defect - Object Detection

Use Case

Welding Defect - Object Detection

Description

Discover the Object Detection dataset, featuring images classified into three categories: bad weld, good weld, and defect

Description:

The Object Detection Dataset for surfaces is designed to identify and classify defects in tasks. This dataset features three distinct classes: “bad weld,” “good weld,” and “defect,” making it ideal for training and evaluating object detection models. It is formatted in the YOLO annotation format, ensuring compatibility with popular object detection frameworks

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The images in this dataset are sourced from a variety of image collections and datasets, offering a diverse range of surface conditions and defect types. This diversity enhances the robustness of model training, allowing for better generalization and performance in real-world scenarios. Researchers and developers can use this dataset to improve automated inspection systems, quality control processes, and defect detection algorithms, ultimately leading to higher standards in welding practices and defect management.