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tags:
  - Image Classification
  - Object Detection
  - Image Recognition
  - Smart Agriculture
  - Garden Maintenance
  - Plant Classification
license: cc-by-nc-sa-4.0
task_categories:
  - image-classification
language:
  - en
pretty_name: Garden Flower Conical Hydrangea Image Recognition Dataset
size_categories:
  - 1B<n<10B

Garden Flower Conical Hydrangea Image Recognition Dataset

With the rapid development of the landscaping industry, garden plants, especially flowers, have a wide variety, making accurate identification and classification a major challenge for the industry. Existing manual identification and traditional image recognition methods have shortcomings such as being time-consuming and having low accuracy. The construction of this dataset aims to enhance the accuracy and efficiency of robotic systems in automatically recognizing garden flowers, addressing key technical issues in automated flower recognition. Data collection was conducted using professional HD cameras under various weather and lighting conditions to ensure sample diversity. The data underwent rigorous multi-round manual annotation and consistency checks, reviewed by botanical experts to ensure high-quality annotation. The annotation team consists of five botanical experts and ten image processing professionals, making it a large-scale operation. Data preprocessing includes image enhancement, noise reduction, and white balance adjustment, and is finally stored and organized in standard JPG format for easy retrieval and access.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
flower_type string The specific type of flower identified in the image.
bloom_stage string The current blooming stage of the flower, such as bud, full bloom, or wilting.
color string The primary color of the flower.
leaf_presence boolean Indicates whether there are leaves present in the image.
background_clarity string The clarity of the image background, described as clear, blurry, etc.
lighting_cond string The lighting conditions during the photo capture, such as sunlight or shade.
image_quality string An assessment of the overall quality of the image, such as high, medium, or low.
number_of_flowers integer The number of flowers present in the image.
flower_health string The health status of the flower, such as healthy, diseased, or damaged.
distance_to_subject float The distance from the capturing device to the flower subject, measured in meters.

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