Industrial Parts Packaging Detection Dataset
#Object Detection #Image Classification #Warehouse Management #Quality Inspection #Anomaly Detection
- 15000 records
- 3.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-16
AI Analysis & Value Prop
The current industrial sector faces significant challenges in managing packaging quality and detecting anomalies in warehouse operations. Existing solutions often rely on manual inspections, which can be time-consuming and prone to human error. This dataset aims to address the need for automated detection of packaging defects, thereby improving efficiency and accuracy in warehouse management. The dataset has been constructed using images captured from various warehouse environments using high-resolution cameras, ensuring a diverse representation of packaging types. Quality control measures included multi-stage annotations, consistency checks among annotators, and reviews by industry experts to ensure high-quality labels. The images are stored in JPEG format, organized in directories based on their respective classes to facilitate easy access and processing.
Dataset Insights
Sample Examples
ef281f46**.jpg|3960*2416|1.95 MB
fc96425e**.jpg|1260*963|64.79 KB
9acef1fd**.jpg|1067*800|38.95 KB
09520187**.jpg|1268*1690|111.93 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| part_type | string | The specific type of industrial part, such as screws, nuts, etc. |
| material_type | string | The material of the industrial part or packaging, such as metal or plastic. |
| defect_presence | boolean | Whether there are any visible defects in the image. |
| defect_type | string | If defects are present, what specific type they are, such as scratches or cracks. |
| dimension_measurements | string | Measurement data for the length, width, height, etc., of parts or packaging. |
| package_condition | string | The condition of the packaging materials, such as intact or damaged. |
| color_info | string | The color of the parts or packaging materials in the image. |
| surface_texture | string | Information about the surface texture of parts or packaging materials. |
| object_count | int | The number of industrial parts or packaging materials detected in the image. |
| orientation | string | The placement direction of the object in the image. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| 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 Industrial Parts Packaging Material Detection Dataset?
- The Industrial Parts Packaging Material Detection Dataset is a high-quality object detection dataset that provides images for detecting packaging materials of industrial parts, aimed at improving detection efficiency and accuracy.
- What are the application scenarios for the Industrial Parts Packaging Material Detection Dataset?
- The dataset can be applied in scenarios such as quality inspection systems on automated production lines, machine vision detection, and industrial automation equipment.
- How to use the Industrial Parts Packaging Material Detection Dataset to optimize detection algorithms?
- The dataset can be used to train deep learning models, which can improve the detection accuracy of algorithms for industrial parts packaging materials, thus enhancing the overall performance of the detection system.
- Which industrial sectors is the Industrial Parts Packaging Material Detection Dataset mainly targeted at?
- The dataset is mainly targeted at the fields of automation detection and quality control in the manufacturing industry.
- What benefits does the Industrial Parts Packaging Material Detection Dataset offer to enterprises?
- By using this dataset, enterprises can increase the level of automation in quality inspection, reduce labor costs, and enhance detection speed and accuracy.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Industrial Parts Packaging Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/dfcfc27fb557712caceda0a8c8542a7e?dataset_scene_id=2},
urldate={2025-08-28},
keywords={Industrial Parts Dataset,Packaging Detection Dataset,Quality Control Images,Warehouse Anomaly Detection},
version={1.0}
}Using this in research? Please cite us.
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