Datasets:
file_name stringclasses 5 values | quality stringclasses 5 values | num_objects stringclasses 1 value | brightness_level stringclasses 1 value | contrast_level stringclasses 3 values | color_distribution stringclasses 5 values | noise_level stringclasses 1 value | object_size_distribution stringclasses 5 values | angle_of_view stringclasses 5 values | image_clarity stringclasses 1 value | object_detection_confidence stringclasses 1 value |
|---|---|---|---|---|---|---|---|---|---|---|
134af7f18e41c23d9981d5a5122247f6.jpg | 1600*1200 | 1 | medium | medium | mainly brown and metallic silver | low | occupies about 1/3 of the image area | about 45 degrees | clear | high |
74bbbfb2ea33db79ba5c4ba491e4fa1e.jpg | 1080*720 | 1 | medium | moderate | mainly gray and silver | low | occupies the medium portion of the image | medium wide-angle | clear | high |
a629dbc4910c382622d050e535dc867c.jpg | 1600*900 | 1 | medium | medium | mainly silver and gray | low | occupies most of the image space | top view | clear | high |
b4aa666c45929534a887825a702d6d3e.jpg | 1200*900 | 1 | medium | slightly high | large areas of gray and silver, some black | low | occupies most of the image | slightly narrow medium | clear | high |
f21a4ce4fe1d4bcfd47cab575167c435.jpg | 3840*2592 | 1 | medium | medium | mainly brown and gray | low | muffler occupies most of the image | frontal view | clear | high |
Silencer Detection Dataset
The current industrial sector faces challenges in maintaining high-quality exhaust systems, particularly in detecting faults in silencers. Existing solutions often rely on manual inspections, which are time-consuming and prone to human error. This dataset aims to address the need for automated detection and noise analysis, providing a foundation for developing machine learning models that can improve accuracy and efficiency in silencer condition assessment. The dataset comprises images captured using high-resolution cameras in controlled environments, ensuring consistent lighting and background conditions. Quality control is enforced through multi-round annotations, consistency checks, and expert reviews. The data is organized in JPG format, with structured metadata for easy access and analysis. The dataset includes 15,000 images, each annotated with specific conditions and noise levels, facilitating detailed analysis and model training.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| num_objects | int | The number of mufflers in the image |
| brightness_level | float | The overall brightness level of the image |
| contrast_level | float | The overall contrast level of the image |
| color_distribution | string | Information about the distribution of pixel colors in the image |
| noise_level | float | The degree of noise present in the image |
| object_size_distribution | string | The size distribution occupied by muffler targets in the image |
| angle_of_view | float | The size of the shooting angle. |
| image_clarity | float | The average clarity information of the image. |
| object_detection_confidence | float | The average confidence of the automatically detected silencer target. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Source & Contact
If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com
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