Asparagus Packaging Recognition Dataset
#Target detection #image classification #Retail detection #automatic recognition #quality control
- Records
- 5000 records
- Size
- 1.5G
- Format
- JPG/PNG/JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
AI Analysis & Value Prop
With the advancement of agricultural modernization, the need for packaging detection of agricultural products such as asparagus is increasing. However, existing automatic recognition systems face challenges such as brand diversity and packaging complexity, leading to low recognition accuracy. This dataset aims to address the accuracy issues in target detection by collecting images of asparagus under different brands and packaging methods. The dataset includes various types of asparagus packaging images, carefully annotated and suitable for packaging detection and automatic recognition in retail scenarios. Data collection was conducted using high-resolution cameras in natural light and standardized environments, combined with both manual and automated annotation processes. For quality control, we implemented multiple rounds of annotation and expert review to ensure consistency and accuracy. Data storage uses JPG format, organized in a directory structure for quick access.
Overview
Dataset Insights
Preview
Sample Examples
b6a386e6**.jpg|4433*5541|3.47 MB
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| asparagus_brand | string | The brand information of asparagus in the image. |
| packaging_type | string | The type of packaging used for the asparagus, such as plastic bags or cardboard boxes. |
| asparagus_quantity | int | The number of asparagus visible in the image. |
| label_visibility | boolean | The visibility status of the label on the asparagus packaging. |
| color_variation | string | The color variation of the asparagus, such as green or purple. |
| package_integrity | boolean | Indicates whether the packaging is intact or not. |
| barcode_present | boolean | Indicates whether there is a barcode present on the packaging. |
Trust
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
FAQ
Frequently Asked Questions
- What scenarios is the Asparagus Packaging Recognition Dataset suitable for?
- This dataset is suitable for scenarios in the retail industry related to the detection and recognition of asparagus packaging, such as automatically identifying different brands of asparagus products in supermarkets.
- Which brands' images are included in the Asparagus Packaging Recognition Dataset?
- The dataset contains images of asparagus from multiple brands, but the specific brand names may vary with updates to the dataset version.
- How to use the Asparagus Packaging Recognition Dataset for object detection?
- To use this dataset for object detection, a deep learning framework like TensorFlow or PyTorch is required, along with relevant object detection algorithms such as YOLO or Faster R-CNN.
- What is the image resolution of the Asparagus Packaging Recognition Dataset?
- The image resolution in the dataset varies due to different capturing devices and processing requirements. Users should check specific specifications before use.
- What machine learning tasks does the Asparagus Packaging Recognition Dataset support?
- This dataset is primarily used for object detection tasks, but it can also be extended to other tasks such as image classification and instance segmentation.
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Cite this Work
@dataset{Mobiusi2025,
title={Asparagus Packaging Recognition Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/08632bd74ff9ab6856516654025f3ae4?dataset_scene_id=5},
urldate={2025-09-15},
keywords={Asparagus packaging recognition, target detection dataset, agricultural dataset, automatic recognition},
version={1.0}
}Using this in research? Please cite us.
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