Mobiusi/Amaryllis-Image-Recognition-Dataset

Amaryllis Image Recognition Dataset

Currently, with the rapid development of the horticulture industry, the diversification and increase in the number of flower varieties pose challenges to flower management. Current solutions such as manual recognition and recording are inefficient and prone to errors. The establishment of the Amaryllis Image Recognition Dataset aims to leverage advanced image recognition technology to achieve fast and accurate flower classification, optimizing garden management processes. Data collection is conducted using high-definition cameras under natural light to ensure the capture of complete plant features. Data quality is ensured through multiple rounds of annotation and consistency checks, performed by a team of experts in the field of botany, comprising more than 10 members. After annotation, the data undergo image enhancement and denoising processing and are finally stored in JPG format, organized in a categorized directory for easy access and model training.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
species_name	string	The name of the Hippeastrum species or variety.
flower_color	string	The color of the Hippeastrum flower.
blooming_stage	string	The blooming stage of the Hippeastrum, such as early bloom, full bloom, or wilting.
plant_health	string	The health status of the Hippeastrum plant, such as healthy, pest-infected, or wilted.
leaf_count	int	The total number of leaves on the Hippeastrum plant.
stem_height	float	The height of the Hippeastrum stem, measured in centimeters.
leaf_color	string	The color of the Hippeastrum leaves.
background_complexity	string	The complexity of the image background, such as simple or complex.
image_clarity	string	The clarity of the image.
lighting_condition	string	The lighting condition during the capture of the Hippeastrum image, such as natural light, shadow, or artificial light.

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