Amaryllis Image Recognition Dataset
#Image Classification #Object Detection #Scene Recognition #Horticulture Management #Flower Classification #Plant Recognition
- 500 records
- 1.5G
- JPG
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
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.
Dataset Insights
Sample Examples
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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 |
Frequently Asked Questions
- What is the main purpose of this dataset?
- The Amaryllis Recognition Image Dataset is primarily aimed at improving flower recognition and classification techniques in the agriculture and forestry sector.
- What types of flowers are covered in this dataset?
- This dataset focuses on the recognition of flowers like Amaryllis.
- How can the Amaryllis Recognition Image Dataset be used to improve machine learning model performance?
- Using this dataset, users can train machine learning models to enhance the accuracy and efficiency of flower recognition.
- What are the specific applications of this dataset in agriculture and forestry?
- The dataset can be used for plant classification, disease detection, and horticultural management.
- What technologies or tools are necessary to use this dataset?
- Analyzing Amaryllis recognition typically requires image processing and machine learning tools such as TensorFlow or PyTorch.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Amaryllis Image Recognition Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/20e6eac14d3b6b6d93c2269edcdada7b},
urldate={2026-02-04},
keywords={Amaryllis recognition, flower image dataset, plant image classification},
version={1.0}
}Using this in research? Please cite us.
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