Crop Pest Region Segmentation Dataset
#target detection #image segmentation #pest monitoring #agricultural pest and disease control #precision agriculture
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-03-13
AI Analysis & Value Prop
The current agricultural sector faces the challenge of frequent pest outbreaks, which not only affect crop yield but also reduce the quality of agricultural products. Existing monitoring methods largely rely on manual inspection, which is inefficient and prone to errors. To improve the accuracy and efficiency of pest monitoring, this dataset offers high-quality pixel-level segmentation annotations of leaf pest regions, aimed at supporting the training and optimization of AI models. The dataset was collected by photographing crop leaves in real farmland with high-resolution cameras to ensure image clarity and detail. Multiple rounds of annotation and consistency checks were employed throughout the annotation process to guarantee data quality and accuracy. The data is stored in PNG/JPG format, with each image corresponding to a segmentation mask, facilitating model training and validation.
Dataset Insights
Sample Examples
020c0fcc**.png|2683*2000|3.91 MB
67c6610b**.png|2752*2000|3.77 MB
346eaeab**.png|2679*2000|3.65 MB
b3799401**.png|1535*2000|2.36 MB
5506998a**.png|1515*2000|3.13 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| crop_type | string | This field specifies the type of crop predominantly present in the image. |
| pest_type | string | This field indicates the main type of pest infestation occurring in the image. |
| visual_symptoms | string | This field lists the visual symptoms caused by pest infestation, such as discoloration, spots, etc. |
| weather_conditions | string | This field includes the weather conditions when the image was taken, such as sunny, cloudy, rainy, etc. |
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 are the application scenarios of the Crop Pest Area Segmentation Dataset?
- This dataset can be used for pest monitoring in agriculture, pest control optimization, and crop health assessment.
- Why is the Crop Pest Area Segmentation Dataset helpful for AI model development?
- The dataset provides precise pixel-level annotations, which help improve the accuracy and robustness of AI models in pest detection and segmentation.
- How is this dataset annotated?
- The dataset uses pixel-level segmentation annotations to ensure each pest area is accurately identified and marked.
- Which agricultural production processes can be improved using the Crop Pest Area Segmentation Dataset?
- It can optimize pest control strategies, increase crop yield and quality, and reduce excessive use of pesticides.
- Who are the main target users of this dataset?
- The main target users include agricultural technology companies, crop research institutions, and enterprises engaged in AI technology development.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Crop Pest Region Segmentation Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/01e38c5af635d15b37f6b549d9a29db9?cate=2},
urldate={2025-09-15},
keywords={crop pests, target detection dataset, agriculture dataset, pest monitoring, image segmentation},
version={1.0}
}Using this in research? Please cite us.
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