Tomato Peduncle Keypoint Dataset
#Target Detection #Key Point Recognition #Plant Monitoring #Agricultural Automation #Fruit Maturity Detection
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-03-13
AI Analysis & Value Prop
In the current agricultural industry, the demand for precise monitoring of plant growth is increasing with the development of smart agriculture. However, existing monitoring techniques often rely on manual recognition, which is inefficient and prone to errors. To address this challenge, the Tomato Peduncle Keypoint Dataset aims to provide high-quality data support for target detection and key point recognition, aiding the development and application of automated monitoring systems. The dataset contains 5000 annotated images of tomato peduncles, all captured from real agricultural environments using high-definition cameras, ensuring data quality. Data quality control measures include multiple rounds of annotation and expert review to ensure the consistency and accuracy of the annotation results. The data is stored in JPG format, organized in a folder structure for ease of subsequent processing and use.
Dataset Insights
Sample Examples
d32d4464**.jpg|3456*5184|1.53 MB
63a3295a**.jpg|3448*4592|2.23 MB
da4ed0c9**.jpg|3456*5184|1.62 MB
a193b330**.jpg|3448*4592|1.58 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| fruit_size | float | The estimated size of the tomato fruit based on the image. |
| color_distribution | string | Information about the color distribution of the tomato in the image. |
| background_conditions | string | Description of the environmental conditions in the image background. |
| lighting_conditions | string | The lighting conditions at the time the image was taken. |
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 agricultural applications is this dataset suitable for?
- The Tomato Peduncle Keypoint Dataset can be used for agricultural smart monitoring, such as fruit growth tracking and pest detection.
- What format are the images in the dataset?
- Images in the Tomato Peduncle Keypoint Dataset are typically provided in JPEG or PNG format, suitable for common image processing use.
- How is the Tomato Peduncle Keypoint Dataset annotated?
- The dataset is annotated with detailed keypoints of tomato peduncles for accurate detection and analysis.
- How can the dataset improve agricultural productivity?
- By automating peduncle detection, the dataset helps achieve real-time monitoring, reduce labor costs, and enhance agricultural productivity.
- Is this dataset suitable for machine learning model training?
- Yes, the Tomato Peduncle Keypoint Dataset is highly suitable for training object detection models, especially for agriculture-related applications.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Tomato Peduncle Keypoint Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/d650aa4d483e1f092d375585b6389f75?dataset_scene_id=5},
urldate={2025-09-15},
keywords={Tomato Peduncle Dataset, Target Detection, Agricultural Automation, Plant Monitoring},
version={1.0}
}Using this in research? Please cite us.
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