Carrot Appearance Inspection Dataset
#Object detection #Image recognition #Crop inspection #Quality control #Smart agriculture
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The current agricultural industry faces challenges such as low crop quality inspection efficiency and high labor costs. Existing inspection methods largely rely on manual visual checks, which are subjective and inefficient. This dataset aims to solve the data scarcity problem in object detection tasks by providing high-quality carrot image data, thereby enhancing the level of automation in smart agriculture. Data collection is conducted using high-resolution cameras in well-lit greenhouse environments to ensure the clarity and recognizability of each image. In terms of quality control, multiple rounds of labeling and expert reviews are employed to ensure labeling accuracy and consistency. All data is stored in JPG format, organized into separate folders by category and quality for ease of subsequent use and retrieval.
Dataset Insights
Sample Examples
a47ca1bd**.jpg|6960*4640|6.85 MB
7f6a37ae**.jpg|4480*6720|3.11 MB
1fa87922**.jpg|7008*4672|6.11 MB
f9adc1c3**.jpg|4272*2400|1.57 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| carrot_color | string | The color of the carrot's surface, such as orange, yellow, etc. |
| carrot_length | float | The length of the carrot, usually measured in centimeters. |
| carrot_diameter | float | The diameter of the carrot, usually measured in centimeters. |
| surface_defects | string | The defect status on the surface of the carrot, such as cracks, spots, etc. |
| defect_severity | string | The severity level of the surface defects, such as mild, moderate, severe. |
| shape_uniformity | string | The uniformity of the carrot's shape, such as regular or irregular. |
| root_tip_condition | string | The condition of the carrot's root tip, such as intact or damaged. |
| green_top_percentage | float | The percentage of the green part at the top of the carrot, usually expressed as a percentage. |
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 main purpose of the Carrot Appearance Detection Dataset?
- The main purpose of the Carrot Appearance Detection Dataset is to enhance the efficiency and accuracy of carrot appearance detection in agricultural production.
- What agricultural applications is this dataset suitable for?
- This dataset is suitable for automated carrot quality inspection, classification, and agricultural product quality control applications.
- What are the benefits of using the Carrot Appearance Detection Dataset?
- Using this dataset can significantly improve the accuracy of carrot appearance detection, reduce errors from manual inspection, and enhance work efficiency.
- What types of image data are included in this dataset?
- The dataset includes images of carrots in various types and quality conditions for model training and testing.
- How does the Carrot Appearance Detection Dataset help increase the automation in agricultural production?
- By providing high-quality object detection data, this dataset can be used to train automated systems, thereby increasing the level of automation in crop management and quality control.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Carrot Appearance Inspection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/8f6b1f8971427743f98344b4b3e26ac7},
urldate={2025-09-15},
keywords={Carrot Inspection, Agricultural Dataset, Object Detection Dataset, Image Recognition, Smart Agriculture},
version={1.0}
}Using this in research? Please cite us.
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