Yard Flower Musella Lasiocarpa Image Recognition Dataset
#Image classification #object detection #pattern recognition #Horticultural plant identification #plant classification #agricultural production management
- 500 records
- 1.6G
- JPG
- CATL
MOBIUSI INC
Updated:2026-04-13
AI Analysis & Value Prop
The horticulture industry involves recognizing and managing a large number of plant species, currently facing challenges in accurately identifying specific flower varieties. Existing solutions mostly rely on human expertise, which can result in poor accuracy and consistency. This dataset aims to improve classification accuracy for machine learning models by providing high-quality images of Musella Lasiocarpa, catering to horticultural management needs. Data collection used high-resolution digital cameras to capture flowers in various growth stages under natural and standard laboratory lighting. Quality control measures include multiple rounds of annotation, expert review of images, consistency checks, and manual validation by personnel with a background in botany. The annotation team consists of 10 botany experts who rigorously ensure data accuracy and consistency. Data preprocessing includes denoising, cropping, and normalization of images, organized by date and flower status, and stored as JPG format files.
Dataset Insights
Sample Examples
6516baff**.jpg|1280*1706|427.29 KB
d45684d9**.jpg|1280*1706|193.89 KB
10be41e1**.jpg|1280*1706|524.29 KB
f4d994e6**.jpg|1280*1706|226.93 KB
f2cbad5e**.jpg|1280*959|241.77 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| flower_type | string | The specific flower species identified in the image, mainly Musella or its variants. |
| growth_stage | string | The growth stage of the flower in the image, such as seedling stage, flowering stage, etc. |
| health_status | string | The health condition of the flower in the image, such as healthy, diseased, or wilted. |
| lighting_condition | string | The lighting condition during capturing, such as natural light, shadow, or bright light. |
| image_background | string | The background environment of the image, such as outdoor, greenhouse, or laboratory. |
| presence_of_pests | boolean | Whether there are pests or signs of pest damage to the flowers in the image. |
| weather_condition | string | The weather condition during the image capture, such as sunny, cloudy, or rainy. |
| leaf_condition | string | The condition of the plant leaves in the image, such as healthy, yellowing, or spotted. |
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 |
Frequently Asked Questions
- What can this dataset be used for?
- The Garden Flower Musella Identification Image Dataset is primarily used for training models to recognize specific flower species, enhancing automated recognition efficiency in agriculture and forestry.
- What is the quality of the images in the dataset?
- The images in the dataset are of high quality, suitable for precise image recognition and classification tasks.
- Who can benefit from this dataset?
- Researchers, agriculture and forestry professionals, and machine learning engineers can all benefit from the application of this dataset by improving the accuracy and efficiency of plant recognition and classification.
- In which projects can the dataset be applied?
- The dataset is applicable in various flower recognition-related projects, such as smart gardening systems, agricultural automation solutions, and environmental monitoring tools.
- Can this dataset be extended to recognize other species of flowers?
- While this dataset focuses on Musella, it can serve as part of a foundational model for developing recognition of other flower species.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Yard Flower Musella Lasiocarpa Image Recognition Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/526558155ba1e5c59b6e6dffc2844163?dataset_scene_cate_type=8},
urldate={2026-02-04},
keywords={Musella Lasiocarpa recognition, flower image dataset, garden plant detection},
version={1.0}
}Using this in research? Please cite us.
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