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file_name
stringclasses
5 values
quality
stringclasses
1 value
flower_species
stringclasses
5 values
color_pattern
stringclasses
5 values
bloom_status
stringclasses
2 values
plant_health
stringclasses
1 value
leaf_characteristics
stringclasses
5 values
flower_count
stringclasses
5 values
background_objects
stringclasses
5 values
light_conditions
stringclasses
1 value
image_quality
stringclasses
4 values
2d36837669c11d1dc8f244d576ea7f55.jpg
1280*1706
White Violet
Petals are white with a yellow center
In full bloom
Healthy
Leaves are green and oval-shaped
3
Green leaves and other colored violets
Natural light
Image is clear with good color reproduction
3c43c2cdfd884ff75e0fa9aa1936996e.jpg
1280*1706
Large-flowered Pansy
White petals with yellow spots in the middle
In Full Bloom
Healthy
Leaves are oval-shaped and green
At least 6 flowers
Background has other purple and white flowers
Natural light
Image is clear with good color reproduction
41c847a2a7f2c3f6cc7d5157e0c11f53.jpg
1280*1706
Unknown species
White petals with yellow spots in the center
In full bloom
Healthy
Leaves are oval-shaped, green
At least five flowers
Other plant leaves
Natural light
Clear, good color rendering
6f42a21ab4dd6f020e14166556960020.jpg
1280*1706
Guessed to be the large-flowered pansy variety, specific subspecies undetermined
Petals are white with yellow spots at the center
In full bloom
Healthy
Leaves are green with slightly serrated edges
Approximately 5 flowers
Other white and purple flowers with green foliage
Natural light
Clear, good color reproduction
cfe924284d3d913f79ce6ab5b038137b.jpg
1280*1706
Pansy
The petals have a combination of white, purple, and blue, with a yellow center
In full bloom
Healthy
Leaves are green and well-shaped
Multiple flowers
Mainly other Pansy plants
Natural light
Clear image with good color reproduction

Pansy Recognition Image Dataset

Currently, garden management faces the challenge of efficiently and accurately identifying flower varieties. Traditional manual identification relies on experience and is inefficient. Existing image recognition technologies still need improvement in the accuracy of specific flower types, especially in complex backgrounds. This dataset aims to address common accuracy deficiencies in pansy recognition by providing a large number of high-quality images to meet the needs of intelligent recognition system development. Data is collected using professional photographic equipment under natural light and various backgrounds to ensure diversity and authenticity. Quality control includes multiple rounds of expert labeling, a combination of machine preliminary classification, and manual review to ensure high labeling precision. The team consists of botany experts and data labeling professionals, with a scale of more than 10 members. In data preprocessing, the latest image enhancement technology is used to improve model training effectiveness. The storage format is JPG, and data is organized by flower category and shooting conditions. The dataset features high precision labeling and consistency in data quality, with a labeling accuracy rate of over 98%. Innovative semi-supervised learning labeling methods are adopted to enhance the dataset's scalability. Compared to similar datasets, this dataset demonstrates stronger application value under diverse and natural collection conditions, particularly in improving the accuracy of flower recognition. It offers greater background diversity and distribution rarity compared to other datasets, suitable for secondary development and application promotion of various intelligent applications, supporting cross-scenario expanded applications.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
flower_species string The specific type or subspecies of the pansy.
color_pattern string The combination and pattern of colors on the pansy petals.
bloom_status string The blooming status of the pansy at the time of the photo, e.g., budding, full bloom.
plant_health string The observed health condition of the pansy plant (healthy, diseased, etc.).
leaf_characteristics string The morphology and color characteristics of the pansy plant leaves.
flower_count integer The number of pansy flowers in the image.
background_objects string Description of the objects in the background surrounding the pansy in the image.
light_conditions string The lighting conditions during the image capture, such as natural light or shadow.
image_quality string The clarity and color reproduction quality of the image.

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

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com

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