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102 Category Flower
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Jun 20, 2021 12:35 PM
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dataset

Overview

We have created a 102 category dataset, consisting of 102 flower categories. The flowers chosen to be flower commonly occuring in the United Kingdom. Each class consists of between 40 and 258 images. The details of the categories and the number of images for each class can be found on this category statistics page.

The images have large scale, pose and light variations. In addition, there are categories that have large variations within the category and several very similar categories. The dataset is visualized using isomap with shape and colour features.

Visualization of the dataset

We visualize the categories in the dataset using SIFT features as shape descriptors and HSV as colour descriptor. The images are randomly sampled from the category.

Shape Isomap

overview-1

Colour Isomap

overview-2

Instruction

The images are contained in the file 102flowers.tgz and the image labels in imagelabels.mat.

We provide 4 distance matrices. D_hsv, D_hog, D_siftint, D_siftbdy. These are the chi^2 distance matrices used in the publication: Automated flower classification over a large number of classes.

Datasplit

The datasplits used in this paper are specified in setid.mat.

The results in the paper are produced on a 103 category database. The two categories labeled Petunia have since been merged since they are the same.

There is a training file (trnid), a validation file (valid) and a testfile (tstid).

Segmentation Images

We provide the segmentations for the images in the file 102segmentations.tgz

More details can be found in: Delving into the whorl of flower segmentation.

Citation

Please use the following citation when referencing the dataset:

@InProceedings{Nilsback08,
  author       = "Maria-Elena Nilsback and Andrew Zisserman",
  title        = "Automated Flower Classification over a Large Number of Classes",
  booktitle    = "Indian Conference on Computer Vision, Graphics and Image Processing",
  month        = "Dec",
  year         = "2008",
}
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🎉Many thanks to Hello Dataset for contributing the dataset
Basic Information
Application ScenariosPlant
AnnotationsCLASSIFICATION
TasksNot Available
LicenseUnknown
Updated on2021-04-07 10:31:19
Metadata
Data TypeImage
Data Volume8.19K
Annotation Amount1
File Size331MB
Copyright Owner
VGG of University of Oxford
Annotator
Unknown
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