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tags:
  - object detection
  - image recognition
  - crop monitoring
  - agricultural production
  - plant health assessment
license: cc-by-nc-sa-4.0
task_categories:
  - image-classification
language:
  - en
pretty_name: Plant Seedling Detection Dataset
size_categories:
  - 1B<n<10B

Plant Seedling Detection Dataset

The agricultural sector currently faces challenges in crop monitoring and pest control, especially during the growth stages of plant seedlings where monitoring accuracy and timeliness are crucial. However, existing detection methods often rely on manual observation, which is inefficient and prone to errors. This dataset aims to address the technical issues of automated detection by providing high-quality plant seedling image data, improving the efficiency of agricultural production. The dataset is constructed using high-resolution cameras to capture seedlings under natural light conditions, ensuring data authenticity and validity. Furthermore, multiple rounds of annotation and expert review ensure data quality and consistency, with the data stored in JPG format for easy subsequent use and sharing. The dataset contains 5000 precisely annotated images, with a total file size of about 1.5G, suitable for training and testing deep learning models.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
growth_stage string The growth stage of the plant seedling, such as germination stage, seedling stage, etc.
leaf_count int The number of leaves on the plant seedling.
leaf_color string The color of the plant leaves, such as green, yellow, brown, etc.
plant_height float The height of the plant seedling, measured in centimeters.
root_visibility boolean The visibility of the roots of the plant seedling.
soil_type string The type of soil where the plant seedling is located, such as clay, sandy soil, etc.

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