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Field Pumpkin Recognition Dataset

The current agriculture industry faces challenges such as low efficiency in crop recognition and difficulty in pest monitoring. Existing solutions often rely on manual identification, which is inefficient and prone to errors. This dataset aims to support the training of machine learning models by providing high-quality pumpkin image data, enhancing the accuracy and speed of pumpkin recognition. Data is primarily collected in the field using high-resolution cameras, ensuring clear and representative images. Data quality control includes multiple rounds of annotation and expert review to ensure consistency and accuracy in annotation. Data is stored in JPG format, organized by category, making it easy for users to find and use. The core advantage of this dataset lies in its high annotation precision (99%), strong annotation consistency, support for large-scale data augmentation techniques, and a 15% improvement in recognition accuracy through optimized algorithms. Additionally, the dataset can be widely applied in scenarios such as agricultural monitoring and precision fertilization, with significant economic benefits.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
pumpkin_type string The type of pumpkin in the image, such as acorn squash, chestnut squash, etc.
maturity_level string The maturity level of the pumpkin in the image, such as immature, mature, or overripe.
color string The primary color of the pumpkin in the image, such as green, yellow, or orange.
size_category string The approximate size category of the pumpkin in the image, such as small, medium, or large.
damage_presence boolean Indicates whether there is visible damage on the surface of the pumpkin in the image.
ambient_conditions string The environmental conditions when the pumpkin was photographed, such as sunny, cloudy, or indoors.

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

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com

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