Steel Pipe Weld Defect Detection with Deep Learning

Serving as for deep learning-based object detection of defects in steel pipe welds. It was created by author huangyebiaoke and last updated in December 2021.

Use Cases

• Train an object detection model to identify weld defect types from images.
• Fine-tune a pre-trained deep learning model for automated visual inspection of steel pipes.
• Analyze the performance of object detection algorithms on industrial weld imagery.

Strengths

• Dataset is associated with a GPL-3.0 license, permitting modification and redistribution.
• Focuses on a specific industrial application of object detection for weld defects.

Limitations

• The dataset size, number of images, and specific defect categories are unknown.
• The data's recency is limited, with the last known update in 2021.

Provenance

Source

github user huangyebiaoke

Collection Method

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Time Range

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Freshness

Last updated 2021-12-06.

Geography

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