New Guinea Impatiens Identification Image Dataset for Garden Flowers
#Image classification #plant identification #computer vision applications #Crop identification #horticultural plant classification #agricultural automation
- 500 records
- 1.2G
- JPG
- CATL
MOBIUSI INC
Updated:2026-09-20
AI Analysis & Value Prop
Currently, the garden flower industry faces challenges such as a wide variety of plant species and high difficulty in identification. Traditional manual identification methods are inefficient and susceptible to subjective influences. This dataset aims to improve the efficiency of identifying New Guinea Impatiens to meet the needs for accurate recognition. In terms of data collection, high-resolution cameras are used to photograph under natural light, ensuring the background is naturally realistic. Quality control is strict, with multiple rounds of manual annotation, expert review, and the annotation team consists of 20 horticultural plant experts. Data preprocessing includes image correction, color balancing, and noise filtering, with the final storage in JPG format and organized by classification.
Dataset Insights
Sample Examples
8add0f02**.jpg|1920*2560|311.08 KB
2565d04a**.jpg|1920*2560|952.21 KB
a693bac6**.jpg|2560*1920|1.17 MB
85311850**.jpg|1920*2560|823.68 KB
de395401**.jpg|1920*2560|474.95 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| species_type | string | The specific species to which the flower belongs. |
| flower_color | string | The primary color of the flower. |
| flower_stage | string | The growth stage of the flower, such as bud, bloom, or wilt. |
| leaf_arrangement | string | The arrangement of leaves, such as whorled or opposite. |
| leaf_shape | string | The shape of the leaves, such as elliptical or lanceolate. |
| petal_count | integer | The number of petals on the flower. |
| stem_length | float | The length of the stem in centimeters. |
| env_condition | string | The environmental conditions at the time of the photo, such as lighting intensity or background objects. |
| image_quality | string | The sharpness of the image, such as high-definition or blurry. |
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 is the Garden Flower New Guinea Impatiens Image Recognition Dataset?
- The Garden Flower New Guinea Impatiens Image Recognition Dataset is a high-quality image dataset designed specifically for recognizing New Guinea Impatiens.
- In which fields can this dataset be applied?
- This dataset is mainly applied in the agricultural and forestry sectors, especially for plant recognition and garden flower research.
- How can the Garden Flower New Guinea Impatiens Image Recognition Dataset be used for plant recognition?
- The dataset can be used by training machine learning models using the images as input to recognize and classify New Guinea Impatiens.
- What are the characteristics of the images in the New Guinea Impatiens Recognition Dataset?
- The dataset includes high-quality images that effectively help improve the accuracy of plant recognition.
- Why choose New Guinea Impatiens as the object of recognition?
- New Guinea Impatiens is a popular ornamental plant, and its recognition is valuable for horticulturists and researchers.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={New Guinea Impatiens Identification Image Dataset for Garden Flowers},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/b412d5ee77bb7f4eee2fcf0c0ea72292},
urldate={2026-02-04},
keywords={New Guinea Impatiens identification, garden flower dataset, agricultural image classification, plant computer vision},
version={1.0}
}Using this in research? Please cite us.
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