Engine Cylinder Body Detection Dataset
#Object Detection #Image Classification #Industrial Inspection #Quality Control
- 15000 records
- 3.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The engine cylinder body inspection industry currently faces challenges including the need for high precision and consistency in defect detection, particularly in complex geometries. Existing solutions often rely on manual inspection, which is time-consuming and prone to human error. This dataset aims to address the technical challenge of automating defect detection through extensive image data capturing various angles of cylinder bodies. The data was collected using high-resolution cameras in controlled factory environments, ensuring clarity and detail. Quality control measures included multi-round annotations, consistency checks among annotators, and expert reviews to ensure data reliability. The dataset is organized in JPG format, with images stored in a structured folder system categorized by defect types.
Dataset Insights
Sample Examples
5c65a6e2**.jpg|1280*902|134.67 KB
f8cd628c**.jpg|1280*924|134.03 KB
c1777039**.jpg|1280*882|99.39 KB
a7f5a858**.jpg|1280*957|146.75 KB
cdd3979d**.jpg|1280*1645|162.99 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| surface_condition | string | The state of the engine block surface, such as smooth, rusty, damaged, etc. |
| defect_type | string | The types of defects that may exist on the engine block, such as cracks or pores. |
| defect_location | string | The specific location of the defect on the engine block. |
| texture_detail | string | Texture information of the engine block surface and its detailed description. |
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 |
Frequently Asked Questions
- What is the engine cylinder block detection dataset?
- The engine cylinder block detection dataset is a collection of multi-angle cylinder block images for object detection tasks, primarily used for training and research of intelligent detection algorithms.
- What are the application scenarios of the engine cylinder block detection dataset?
- This dataset is mainly applied in industrial smart detection systems, such as quality control and defect detection of cylinder blocks in automotive manufacturing.
- What images are included in the engine cylinder block detection dataset?
- The dataset includes multi-angle detection images of cylinder blocks, covering engine blocks photographed from different perspectives.
- Why choose the engine cylinder block detection dataset for research?
- Using this dataset for research can help develop more accurate intelligent detection algorithms, improving detection efficiency and quality in industrial production.
- How does the engine cylinder block detection dataset support the development of intelligent detection algorithms?
- The dataset supports this by providing real-world detection images to help train models to identify and detect specific features and potential defects in cylinder blocks.
- What are the advantages of using the engine cylinder block detection dataset?
- Using this dataset provides detection data under real-world conditions, enhancing the reliability and applicability of algorithms.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Engine Cylinder Body Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/dc1c617be7e52d0890d16ac3ccc33439},
urldate={2025-08-28},
keywords={engine cylinder detection,industrial inspection dataset,image dataset for quality control},
version={1.0}
}Using this in research? Please cite us.
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