Garden Flower Digitalis Recognition Image Dataset
#image classification #object detection #plant species identification #plant recognition #horticultural management #agroforestry monitoring
- 500 records
- 1.5G
- JPG
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
In modern horticultural management, accurate identification and monitoring of garden plant species is crucial. However, existing techniques often face issues such as insufficient image resolution and the time-consuming and inaccurate nature of manual recognition. This dataset aims to improve the accuracy and efficiency of automated recognition by providing high-quality images of Digitalis. The images in the dataset were collected from various horticultural locations using high-resolution cameras under natural light and from multiple angles. The quality control process includes multiple rounds of manual annotation and expert consistency review. The annotation team is composed of professionals in botany and horticulture, ensuring accuracy and professionalism in the annotations. Data preprocessing methods including standardization and augmentation have been applied to enhance model training effectiveness. All images are stored in an orderly hierarchical structure, facilitating quick retrieval and classification.
Dataset Insights
Sample Examples
818b779d**.jpg|1280*1706|281.81 KB
226db386**.jpg|1280*1706|454.25 KB
7fa2c1aa**.jpg|1280*1706|240.26 KB
a7ca739b**.jpg|1280*1706|298.58 KB
7f3badf5**.jpg|1280*1706|527.51 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| species_name | string | The specific species name of the Digitalis in the image. |
| flower_color | string | The main color of the Digitalis flowers in the image. |
| plant_height | float | The estimated height of the Digitalis plant in the image (in cm). |
| leaf_arrangement | string | The arrangement of the Digitalis leaves in the image. |
| flower_count | integer | The number of flowers on the Digitalis in the image. |
| bloom_stage | string | The bloom stage of the Digitalis in the image (e.g., budding, full bloom, wilting). |
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 varieties of foxglove does this dataset mainly include?
- This dataset mainly includes images of common garden varieties of foxglove for identification and classification purposes.
- How can the Garden Flower Foxglove Identification Image Dataset be used in research?
- Researchers can use this dataset to train machine learning models for identifying and classifying foxgloves in real-world scenarios.
- What is the image quality in the Garden Flower Foxglove Identification Image Dataset?
- The images in this dataset are high-quality, suitable for accurate identification and classification of garden flowers.
- How can this dataset assist in garden design?
- This dataset can help garden designers better identify and select foxglove varieties suitable for horticultural layouts.
- Why is foxglove identification important in the agriculture and forestry sector?
- Accurate identification of foxgloves can help agriculture and forestry workers manage plant resources, design landscapes, and enhance biodiversity.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Garden Flower Digitalis Recognition Image Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/b481a2f8d73c04e097a18adfb7850ba2},
urldate={2026-02-04},
keywords={garden flower recognition, Digitalis image dataset, plant classification data, agroforestry image classification},
version={1.0}
}Using this in research? Please cite us.
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