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Mobiusi/Mold-Template-Defect-Recognition-Dataset

Mold Template Defect Recognition Dataset In the industrial sector, mold quality inspection is crucial for ensuring product integrity but faces challenges such as inconsistent defect detection and high rates of false negatives. Existing solutions often rely on manual inspection, which is time-consuming and prone to human error, leading to inefficiencies. This dataset aims to address these challenges by providing a comprehensive collection of labeled images that enhance machine… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Mold-Template-Defect-Recognition-Dataset.

sourceHugging Facecc-by-nc-sa-4.0updated 7mo agoView on Hugging Face

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Dataset Card

Mold Template Defect Recognition Dataset

In the industrial sector, mold quality inspection is crucial for ensuring product integrity but faces challenges such as inconsistent defect detection and high rates of false negatives. Existing solutions often rely on manual inspection, which is time-consuming and prone to human error, leading to inefficiencies. This dataset aims to address these challenges by providing a comprehensive collection of labeled images that enhance machine learning models for accurate defect recognition in mold templates. Data was collected using high-resolution cameras in controlled industrial environments, ensuring clarity and consistency. Quality control measures included multiple rounds of labeling, consistency checks among annotators, and expert reviews to maintain high accuracy. The images are stored in JPG format, organized in directories by defect type, facilitating easy access and processing.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
defect_type	string	The types of defects appearing on the mold, such as cracks and pores.
defect_location	string	A detailed description of the defect's specific location on the mold.
severity_level	integer	The severity level of the defect as defined by the standards.
boundingboxcoordinates	string	Coordinates of the bounding box that marks the defect in the target detection task.
surface_condition	string	The overall condition of the mold surface, including the presence of oxidation or wear.
light_condition	string	The lighting conditions when capturing the image, such as natural light or artificial light.
image_quality	string	The quality assessment of the image, such as clarity or blurriness.

Compliance Statement

<table> <tr> <td>Authorization Type</td> <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td> </tr> <tr> <td>Commercial Use</td> <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td> </tr> <tr> <td>Privacy and Anonymization</td> <td>No PII, no real company names, simulated scenarios follow industry standards</td> </tr> <tr> <td>Compliance System</td> <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td> </tr> </table>

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com