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4 values
quality
stringclasses
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object_count
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weather_conditions
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grassland
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grass, person
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0.8
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Field Grass Navigation Dataset

The current agricultural industry faces challenges in crop health monitoring and weed management, particularly in large farmland areas where effective automated tools for detecting and classifying crops and weeds are lacking. Existing solutions often rely on manual monitoring, which is inefficient and prone to errors. Therefore, the Field Grass Navigation Dataset aims to provide high-quality annotated images to support research and applications in object detection and image segmentation. The dataset is constructed by capturing images in real farmland environments with high-resolution cameras, employing multiple rounds of annotation and expert reviews to ensure accuracy and consistency of annotations, and is stored in JPG format for convenient subsequent processing and analysis.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
object_type string The type of agricultural-related object detected in the image, such as tractor, grassland, crops, etc.
object_count integer The number of agricultural-related objects in the image.
vegetation_density float The vegetation coverage of grassland or crops in the image, ranging from 0 to 1.
image_lighting string The lighting conditions of the image, such as sunny, cloudy, or nighttime.
weather_conditions string The weather conditions when the image was taken, such as sunny, rainy, or snowy.
tractor_presence boolean Indicates whether a tractor is present in the image.

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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