Mobiusi

Camellia Recognition Image Dataset for Garden Flowers

#Image classification #species recognition #computer vision #Plant recognition #camellia variety classification #garden management
  • 500 records
  • 1.5G
  • JPG
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-02-04

AI Analysis & Value Prop

Currently, garden flower recognition plays an important role in smart agriculture and horticulture management. However, with many camellia varieties that appear similar, recognition becomes difficult. Existing solutions often rely on a small number of samples or manual experience, which limits accuracy. This dataset aims to improve recognition algorithm accuracy with extensive camellia image resources, meeting the needs of automated recognition business requirements. Data collection is conducted with high-resolution cameras, covering various camellia varieties and different blooming stages to ensure sample diversity and representativeness. Quality control involves multiple rounds of annotation and expert review, with an annotation team consisting of botanists and image recognition experts. The data format is JPG, structurally stored with detailed annotation files. Data preprocessing involves image enhancement and normalization steps to enhance training effectiveness.

Dataset Insights

Sample Examples

462bda66**.jpg|4080*3060|1.14 MB

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cb08c1ba**.jpg|3060*4080|1.28 MB

c67075f1**.jpg|4080*3060|1.05 MB

e7ec8111**.jpg|4080*3060|761.57 KB

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
flower_speciesstringThe specific species of camellia depicted in the image.
flower_colorstringThe color of the camellia depicted in the image.
flower_stagestringThe growth stage of the camellia depicted in the image, such as bud, half-bloom, full-bloom.
image_sharpnessfloatThe clarity score of the image, ranging from 0 to 1.
background_clutterintegerThe complexity score of the image background, where 0 represents a plain background and 1-5 indicates varying levels of clutter.
lighting_conditionsstringThe lighting conditions during the image capture, such as daylight, cloudy, indoor lighting.
image_orientationstringThe orientation of the image, such as landscape (horizontal) or portrait (vertical).

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What projects is the Garden Camellia Recognition Image Dataset suitable for?
This dataset is suitable for training and testing plant recognition algorithms, research on camellia variety classification, development of agricultural and forestry related image recognition applications, and support projects for garden management systems.
How to use this dataset to improve plant recognition ability?
By using this dataset to train machine learning models, the accuracy of recognizing camellias and other similar flowers can be improved. The diverse samples in the dataset help enhance the model's ability to recognize camellias in different environments and perspectives.
What are the applications of this dataset in agriculture, forestry, and fisheries?
In agriculture, forestry, and fisheries, this dataset can be used for automated plant classification, garden plant management, research on camellia cultivation techniques, and plant recognition and statistics in ecological monitoring.
How is this dataset constructed?
This dataset is constructed by collecting high-quality photos of camellias in various environments, ensuring coverage of different varieties, colors, blooming states, and shooting angles to provide a rich training set for machine learning models.
What should be considered when using this dataset for research?
When using this dataset for research, it is important to consider the image quality and label accuracy in the dataset. Researchers should also ensure compliance with data usage agreements and respect data privacy and usage rights.

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Cite this Work

@dataset{Mobiusi2026,
  title={Camellia Recognition Image Dataset for Garden Flowers},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/6f2931654389007465c0106733a627ff?dataset_scene_cate_type=8},
  urldate={2026-02-04},
  keywords={Camellia recognition, garden flower image dataset, plant classification training data},
  version={1.0}
}

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