Evergreen Euphorbia Image Recognition Dataset
#Image Classification #Species Recognition #Feature Extraction #Plant Recognition #Garden Management #Agricultural and Forestry Monitoring
- 500 records
- 1.5G
- JPG
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
In modern agriculture and forestry, plant species recognition is an important task for improving agricultural efficiency and maintaining the ecological environment. However, traditional manual recognition methods are time-consuming and prone to errors, especially under variable natural conditions that add complexity to plant recognition. Current plant recognition software is often limited by insufficiently diverse data sources, which makes it difficult to improve recognition accuracy. The Evergreen Euphorbia Image Recognition Dataset aims to provide high-quality, diverse plant images for training more precise recognition models. Data collection uses high-resolution cameras to shoot in different seasons and lighting conditions to ensure image quality. Multiple rounds of labeling and consistency checks are conducted by a team of botanical experts to ensure the accuracy of the data labels. The labeling team consists of 10 industry experts with years of experience in plant classification. Data preprocessing includes image enhancement, denoising, and standardization, stored in JPEG format.
Dataset Insights
Sample Examples
a78dcc28**.jpg|1920*2560|345.16 KB
a69cdd04**.jpg|1920*2560|601.25 KB
7e851a6a**.jpg|1920*2560|671.45 KB
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Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| plant_species | string | The species of plant shown in the image. |
| leaf_color | string | The color of the leaves of the plant in the image. |
| flower_presence | boolean | Indicates whether the plant in the image has flowers. |
| flower_color | string | The color of the flowers of the plant in the image. |
| number_of_flowers | integer | The number of visible flowers in the image. |
| plant_health | string | The health condition of the plant, such as healthy, unhealthy, or wilting. |
| growth_stage | string | The growth stage of the plant, such as seedling or mature. |
| background_scene | string | The background scene in the image, such as garden or indoor. |
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 field of study is this dataset suitable for?
- The Evergreen Spurge Recognition Image Dataset is suitable for research in agriculture, forestry, and fisheries, particularly studies related to plant recognition and classification.
- What capability can this dataset help improve?
- This dataset can help improve the accuracy of recognizing agricultural and forest plants, especially evergreen spurge.
- What skills are needed to use this dataset?
- To effectively use this dataset, users may need to have skills in machine learning, image processing, or botany.
- What type of image data does the dataset include?
- The dataset includes images of evergreen spurge for research and applications in plant recognition.
- Who might be interested in this dataset?
- Botanists, agricultural and forestry researchers, and scientists using machine learning for image recognition may be interested in this dataset.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Evergreen Euphorbia Image Recognition Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/a30ffce327c02d0efeb79078ee2d1233},
urldate={2026-02-04},
keywords={Plant Recognition Dataset, Garden Flower Data, Evergreen Euphorbia Recognition},
version={1.0}
}Using this in research? Please cite us.
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