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tags:
  - image classification
  - plant disease detection
  - intelligent planting management
  - garden flower management
  - agricultural technology applications
  - plant recognition systems
license: cc-by-nc-sa-4.0
task_categories:
  - image-classification
language:
  - en
pretty_name: Pansy Recognition Image Dataset
size_categories:
  - 1B<n<10B

Pansy Recognition Image Dataset

Currently, garden management faces the challenge of efficiently and accurately identifying flower varieties. Traditional manual identification relies on experience and is inefficient. Existing image recognition technologies still need improvement in the accuracy of specific flower types, especially in complex backgrounds. This dataset aims to address common accuracy deficiencies in pansy recognition by providing a large number of high-quality images to meet the needs of intelligent recognition system development. Data is collected using professional photographic equipment under natural light and various backgrounds to ensure diversity and authenticity. Quality control includes multiple rounds of expert labeling, a combination of machine preliminary classification, and manual review to ensure high labeling precision. The team consists of botany experts and data labeling professionals, with a scale of more than 10 members. In data preprocessing, the latest image enhancement technology is used to improve model training effectiveness. The storage format is JPG, and data is organized by flower category and shooting conditions. The dataset features high precision labeling and consistency in data quality, with a labeling accuracy rate of over 98%. Innovative semi-supervised learning labeling methods are adopted to enhance the dataset's scalability. Compared to similar datasets, this dataset demonstrates stronger application value under diverse and natural collection conditions, particularly in improving the accuracy of flower recognition. It offers greater background diversity and distribution rarity compared to other datasets, suitable for secondary development and application promotion of various intelligent applications, supporting cross-scenario expanded applications.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
flower_species string The specific type or subspecies of the pansy.
color_pattern string The combination and pattern of colors on the pansy petals.
bloom_status string The blooming status of the pansy at the time of the photo, e.g., budding, full bloom.
plant_health string The observed health condition of the pansy plant (healthy, diseased, etc.).
leaf_characteristics string The morphology and color characteristics of the pansy plant leaves.
flower_count integer The number of pansy flowers in the image.
background_objects string Description of the objects in the background surrounding the pansy in the image.
light_conditions string The lighting conditions during the image capture, such as natural light or shadow.
image_quality string The clarity and color reproduction quality of 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