Cabbage Pest Identification Dataset
#object detection #image classification #crop monitoring #pest identification #precision agriculture
- 20000 records
- 3.8G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-10-14
AI Analysis & Value Prop
The current agriculture industry faces a severe threat to crop yield and quality from pests, and traditional pest identification methods are inefficient and prone to errors, unable to meet the demands of modern agriculture for precise monitoring. Existing solutions often rely on manual identification, which is costly in terms of labeling and lacks real-time capabilities. This dataset aims to provide an efficient pest detection solution through image recognition technology, improving the intelligence level of agricultural production. The dataset contains various pest images, collected with high-definition cameras in different environments, with quality control to ensure labeling consistency and accuracy. The data is stored in JPEG format and organized in a folder structure for quick access and processing.
Dataset Insights
Sample Examples
cf66ff2a**.jpg|8368*5584|6.83 MB
032c3084**.jpg|4196*5067|3.86 MB
8d3c5e93**.jpg|3840*2560|1.89 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| infestation_level | string | The severity level of pest infestation in the image, e.g., light, moderate, severe. |
| pest_count | int | The total number of pests identified in the image. |
| health_status | string | The health status of the cabbage based on its appearance in the image, such as healthy, damaged, diseased. |
| damage_type | string | The specific type of damage on the cabbage caused by pest infestation as seen in the image. |
| leaf_condition | string | The condition of cabbage leaves as observed in the image, such as intact, missing parts, discolored. |
| growth_stage | string | The growth stage of the cabbage as depicted in the image, e.g., seedling, growing, mature. |
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 types of pest images are included in the Cabbage Pest Identification Dataset?
- The dataset mainly includes images of common cabbage pests such as cabbage worms and aphids, aiding in identification and monitoring.
- How can the Cabbage Pest Identification Dataset aid in precision agriculture?
- By analyzing pest images in the dataset, intelligent identification systems can be developed to enhance monitoring accuracy, thus optimizing crop management.
- How is object detection technology applied in the Cabbage Pest Identification Dataset?
- Object detection technology can automatically identify pest types and locations in images, providing technical support for agricultural automation.
- What is the relationship between the Cabbage Pest Identification Dataset and smart agriculture?
- This dataset provides training data for smart agriculture systems aiming to improve pest identification efficiency and reduce production losses.
- How does the Cabbage Pest Identification Dataset advance agricultural monitoring?
- The extensive pest images in the dataset can train machine learning models, improving automation and precision in agricultural monitoring systems.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Cabbage Pest Identification Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/dfb6c6977a41559b7832eb425dff7934},
urldate={2025-09-15},
keywords={cabbage pest, pest identification, agricultural dataset, object detection, precision agriculture},
version={1.0}
}Using this in research? Please cite us.
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