• Description:

The Oxford Flowers 102 dataset is a consistent of 102 flower categories commonly occurring in the United Kingdom. Each class consists of between 40 and 258 images. 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 divided into a training set, a validation set and a test set. The training set and validation set each consist of 10 images per class (totalling 1020 images each). The test set consists of the remaining 6149 images (minimum 20 per class).

Split Examples
'test' 6,149
'train' 1,020
'validation' 1,020
  • Feature structure:
    'file_name': Text(shape=(), dtype=string),
    'image': Image(shape=(None, None, 3), dtype=uint8),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=102),
  • Feature documentation:
Feature Class Shape Dtype Description
file_name Text string
image Image (None, None, 3) uint8
label ClassLabel int64


  • Citation:
   author = "Nilsback, M-E. and Zisserman, A.",
   title = "Automated Flower Classification over a Large Number of Classes",
   booktitle = "Proceedings of the Indian Conference on Computer Vision, Graphics and Image Processing",
   year = "2008",
   month = "Dec"