Onion Classification and Segmentation Dataset

#Semantic Segmentation #Image Classification #Crop Classification #Pest and Disease Detection #Image Recognition

5000 records
1.5G
JPG/PNG/JSON
CC-BY-NC-SA 4.0
MOBIUSI INC

Updated:2026-03-13

AI Analysis & Value Prop

The current agricultural industry faces challenges of high cost and low efficiency in crop monitoring and pest and disease detection. Existing solutions often rely on manual inspection, which is inefficient and prone to errors. This dataset aims to enhance the application capability of computer vision models in agriculture by providing high-quality onion images and segmentation annotations. The dataset construction process includes using professional cameras to shoot onion images under natural light conditions, and ensuring annotation consistency and accuracy through multiple rounds of annotation and expert review. Data will be stored in JPG format for original images and in JSON format for the corresponding mask information, facilitating subsequent deep learning training.

Dataset Insights

Sample Examples

baf9f591**.jpg|3648*5472|2.97 MB

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
object_class	string	The type of onion present in the image.
disease_presence	boolean	Indicates whether a disease is detected on the onion in the image.
lighting_conditions	string	A description of the lighting conditions when the image was taken.
growth_stage	string	The growth stage of the onion, such as seedling stage, maturity stage, etc.
surface_texture	string	A description of the surface texture characteristics of the onion.
defect_details	string	A description of any defects regarding the appearance or health of the onion.

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 Onion Classification and Segmentation Dataset?: The Onion Classification and Segmentation Dataset is an image dataset designed for the agriculture sector, aimed at enhancing the intelligence of crop classification and pest detection.

What is the purpose of the Onion Classification and Segmentation Dataset?: The main purpose of this dataset is to promote research work in the field of agriculture, particularly in applications regarding crop classification and pest detection.

How does this dataset help improve crop classification and pest detection?: By providing high-quality image data, researchers can use this dataset to train machine learning models, thus improving the efficiency and accuracy of crop classification and pest detection.

Why choose semantic segmentation as the dataset type?: Semantic segmentation allows for the classification of every pixel in an image, which is especially important for accurately identifying and classifying different crop areas.

What types of algorithm research is this dataset suitable for?: The Onion Classification and Segmentation Dataset is suitable for various algorithmic research in computer vision, especially those related to deep learning and convolutional neural networks.

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Cite this Work

@dataset{Mobiusi2025,
  title={Onion Classification and Segmentation Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/08ae71b7be4c0d4fdaf15c803b4ab044},
  urldate={2025-09-15},
  keywords={Onion Classification Dataset, Semantic Segmentation Dataset, Agricultural Image Processing, Pest and Disease Detection},
  version={1.0}
}

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