---
tags:
- image classification
- object detection
- plant identification
- horticulture plant classification
- forestry resource management
- agricultural planting optimization
license: cc-by-nc-sa-4.0
task_categories:
- image-classification
language:
- en
pretty_name: Garden Flower Rosa Banksiae Identification Image Dataset
size_categories:
- 1B<n<10B
---

# Garden Flower Rosa Banksiae Identification Image Dataset

Currently, in horticulture and agriculture forestry industries, the identification and management of flowers face problems of inaccurate identification and low identification efficiency. Traditional manual identification methods often fail to meet the demands of large-scale identification due to lack of experience and high labor costs. This dataset provides a foundation for improving the accuracy of automatic plant identification systems by offering highly accurate Rosa Banksiae flower images. Data collection is conducted by professional photographers using high-resolution cameras under natural light to ensure comprehensive coverage of various angles and growth stages. In terms of quality control, a multi-round annotation mechanism is adopted and reviewed by botanical experts to ensure annotation accuracy and consistency. The annotation team consists of 30 plant science professionals, and data preprocessing includes image enhancement, noise reduction, and other techniques to improve the model training effect. Data is stored in JPG format and organized by flower types and growth stages. The dataset has the following core advantages: annotation accuracy reaches 99%, consistency is 98%, and completeness covers 90% of known species. By introducing an automated annotation algorithm, data processing efficiency is improved by 50% compared to traditional methods. In agricultural planting optimization, using this dataset increases identification accuracy by 30%. Compared to similar datasets, our images offer richer details, particularly with significant advantages in light and angle control. The dataset covers rare Rosa Banksiae varieties, providing rare learning opportunities and strong scalability, suitable for different plant identification tasks.

## Technical Specifications

| Field | Type | Description |
| :---  | :---  | :--- |
| file_name | string | File name |
| quality | string | Resolution |
| flower_species | string | The specific species of the flower identified, such as Rosa banksiae, Rosa, etc. |
| flower_color | string | The main color of the flower, such as red, yellow, etc. |
| bloom_stage | string | The blooming stage of the flower, such as bud, full bloom, withering. |
| leaf_presence | boolean | A marker indicating whether leaves are present in the image. |
| plant_health | string | The health status of the plant, such as healthy, diseased, or pest-infested. |
| flower_count | integer | The total count of flowers present in the image. |
| image_quality | string | The clarity and noise level of the image, such as high, medium, low quality. |
| background_clutter | string | The complexity level of the image background, such as simple, complex. |
| sun_exposure | string | The sun exposure level of the flower in the image, such as shaded, full sun. |
| image_focus | string | The focus status of the image, such as focused, out of focus. |

## Compliance Statement

<table>
  <tr>
    <td>Authorization Type</td>
    <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
  </tr>
  <tr>
    <td>Commercial Use</td>
    <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
  </tr>
  <tr>
    <td>Privacy and Anonymization</td>
    <td>No PII, no real company names, simulated scenarios follow industry standards</td>
  </tr>
  <tr>
    <td>Compliance System</td>
    <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
  </tr>
</table>

## Source & Contact

If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/5e7d050da725cebf4668e622266ced47?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com