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shangzx/Exhaust-Pipe-Detection-Dataset

Exhaust Pipe Detection Dataset The current industrial sector faces significant challenges in ensuring the quality and proper assembly of exhaust systems, particularly with the risk of misassembled exhaust pipes leading to performance issues and environmental concerns. Existing solutions often lack the capability to accurately detect these misassemblies in real-time, leading to inefficiencies and potential safety hazards. This dataset aims to address these technical challenges by… See the full description on the dataset page: https://huggingface.co/datasets/shangzx/Exhaust-Pipe-Detection-Dataset.

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

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Dataset Card

Exhaust Pipe Detection Dataset

The current industrial sector faces significant challenges in ensuring the quality and proper assembly of exhaust systems, particularly with the risk of misassembled exhaust pipes leading to performance issues and environmental concerns. Existing solutions often lack the capability to accurately detect these misassemblies in real-time, leading to inefficiencies and potential safety hazards. This dataset aims to address these technical challenges by providing high-quality images of exhaust pipes, labeled for various assembly errors and layout confirmations. The data was collected using high-resolution cameras in controlled factory environments, ensuring optimal lighting and consistency. Quality control measures include multiple rounds of annotation, inter-annotator agreement checks, and reviews by domain experts. The images are stored in JPG format, organized by folders corresponding to different error types.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
pipe_position	string	Description of the position of the exhaust pipe in the image.
connection_status	string	The actual connection status of the exhaust pipe, whether there is any misinstallation.
exhaustsystemlayout	string	Description of the overall layout of the exhaust system.
defect_severity	integer	If there is a defect, the severity rating of the defect.
object_count	integer	The number of exhaust pipes and related components detected in the image.
anomaly_type	string	Description of the detected type of anomaly.
image_quality	string	Assessment of the clarity and overall quality of the image.
color_consistency	string	Consistency of the exhaust pipe with its expected color.
corrosion_status	string	Description of the corrosion or wear condition on the surface of the exhaust pipe.
part_visibility	string	Visibility and degree of occlusion of components in the image.

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

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