Garden Flower Conical Hydrangea Image Recognition Dataset
#Image Classification #Object Detection #Image Recognition #Smart Agriculture #Garden Maintenance #Plant Classification
- Records
- 500 records
- Size
- 1.2G
- Format
- JPG
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
AI Analysis & Value Prop
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.
Overview
Dataset Insights
Preview
Sample Examples
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Schema
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. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
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
FAQ
Frequently Asked Questions
- What is the Garden Flowers Cone Hydrangea Recognition Image Dataset?
- The Garden Flowers Cone Hydrangea Recognition Image Dataset is an image dataset specifically developed for robotic vision systems to recognize and classify cone hydrangea plants.
- Which industry field is this dataset suitable for?
- This dataset is suitable for the agricultural, forestry, and fisheries industry, especially for horticulture and plant recognition applications.
- What is the primary use of the Garden Flowers Cone Hydrangea Recognition Image Dataset?
- It is primarily used for training and testing robotic vision systems to accurately recognize and classify cone hydrangea flower varieties.
- How can the Garden Flowers Cone Hydrangea Recognition Image Dataset be used for research?
- Researchers can use this dataset to train image classification models to improve robotic recognition capabilities in real-world scenarios.
- How does the Garden Flowers Cone Hydrangea Recognition Image Dataset help improve robotic vision systems?
- By providing a large amount of high-quality recognition image data to train AI models, it enhances recognition accuracy and system stability.
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Cite this Work
@dataset{Mobiusi2026,
title={Garden Flower Conical Hydrangea Image Recognition Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/bdbd09b1c445bcac025166325b3e95ba?dataset_scene_cate_type=8},
urldate={2026-02-04},
keywords={Garden Flower Recognition, Robotic Vision Dataset, Conical Hydrangea Images},
version={1.0}
}Using this in research? Please cite us.
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