Standard DatasetsMachine Part Defects Segmentation Dataset
The "Machine Part Defects Segmentation Dataset" is designed for the manufacturing industry, consisting of internet-collected images, all with a resolution of 1000 x 1000 pixels. This dataset focuses on binary segmentation to identify white defects on machine parts, providing clear annotations that highlight areas of concern for quality control and inspection processes.
Sample
Specification
Dataset ID
MD-Image-042
Dataset Name
Machine Part Defects Segmentation Dataset
Data Type
ImageVolume
About 120k
Data Collection
Internet collected images. Resolution is 1000 x 1000
Annotation
Binary Segmentation
Annotation Notes
Annotate the White Defects of the machine part.
Application Scenarios
Manufacturing
Data Collections
This dataset includes around 120k images, each dedicated to showcasing defects in machine parts. The binary segmentation approach specifically annotates white defects, making it straightforward for automated systems to detect and assess the severity of these imperfections. This resource is invaluable for manufacturers looking to enhance quality assurance protocols, streamline inspection processes, and reduce the incidence of faulty components in production lines.
Quality Assurance
Related products
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