Raspberry Fruit Detection Dataset

#object detection #image recognition #crop monitoring #fruit maturity assessment #smart agriculture
  • 5000 records
  • 1.5G
  • JPG/PNG/JSON
  • CATL
  • MOBIUSI INCMOBIUSI INC
Updated:2026-04-14

AI Analysis & Value Prop

The current agricultural industry faces the difficult problem of fruit detection, especially in terms of fruit maturity assessment and pest monitoring. Traditional manual detection methods are inefficient and prone to errors. Existing solutions often rely on manual annotation and imprecise detection models, resulting in identification accuracy and efficiency that fail to meet actual needs. This dataset aims to provide a high-quality fruit detection dataset to improve the accuracy and reliability of automated detection technologies. The data is captured using high-resolution cameras under natural lighting conditions, covering raspberry fruits in various growth stages. The dataset has undergone multiple rounds of annotation and expert review to ensure the accuracy and consistency of annotations, stored in JPG format, organized by category and shooting time.

Dataset Insights

Sample Examples

5e6ab1fb**.jpg|4160*6240|1.73 MB

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
fruit_countintThe number of raspberry fruits in the image.
ripe_fruit_countintThe number of ripe raspberry fruits in the image.
unripe_fruit_countintThe number of unripe raspberry fruits in the image.
average_fruit_sizefloatThe average size of raspberry fruits in the image.
fruit_densityfloatThe density of raspberry fruits in the image, calculated as fruits per unit area.
leaf_countintThe number of raspberry plant leaves in the image.
plant_health_statusstringThe assessed health status of raspberry plants as depicted in the image.
sunlight_exposurestringThe level of sunlight exposure affecting raspberry fruits as depicted in the image.

Compliance Statement

Authorization TypeProprietary - Commercial AI Training License (No Redistribution)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What are the application scenarios for the raspberry fruit detection dataset?
This dataset is suitable for agricultural intelligent monitoring, fruit yield prediction, and pest and disease identification.
How was the raspberry fruit detection dataset collected?
The dataset was collected by capturing images of raspberry fruits using professional agricultural monitoring equipment and annotating them to form an object detection dataset.
What are the main features of the raspberry fruit detection dataset?
The main features of this dataset include high-resolution images, accurately annotated detection areas, and its suitability for various intelligent agricultural applications.
What agricultural issues can be addressed using the raspberry fruit detection dataset?
This dataset can help agricultural practitioners automate fruit monitoring, improve yield estimation accuracy, and provide early pest and disease warnings.
What is the significance of the raspberry fruit detection dataset in agriculture?
In agriculture, the significance of this dataset lies in its role as a key tool for enhancing production efficiency and improving fruit quality.

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Cite this Work

@dataset{Mobiusi2025,
  title={Raspberry Fruit Detection Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/53cf6d5ff2e1e5483575160b8e45a704?cate=2},
  urldate={2025-09-15},
  keywords={raspberry fruit detection, agricultural dataset, object detection dataset, smart agriculture},
  version={1.0}
}

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