OXFORD-IIIT PET Dataset
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Omkar M Parkhi, Andrea Vedaldi, Andrew Zisserman and C. V. Jawahar

We have created a 37 category pet dataset with roughly 200 images for each class. 
The images have a large variations in scale, pose and lighting. All images have an 
associated ground truth annotation of breed, head ROI, and pixel
level trimap segmentation.

Contents:
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trimaps/ 	Trimap annotations for every image in the dataset
		Pixel Annotations: 1: Foreground 2:Background 3: Not classified
xmls/		Head bounding box annotations in PASCAL VOC Format

list.txt	Combined list of all images in the dataset
		Each entry in the file is of following nature:
		Image CLASS-ID SPECIES BREED ID
		ID: 1:37 Class ids
		SPECIES: 1:Cat 2:Dog
		BREED ID: 1-25:Cat 1:12:Dog
		All images with 1st letter as captial are cat images while
		images with small first letter are dog images.
trainval.txt	Files describing splits used in the paper.However,
test.txt	you are encouraged to try random splits.



Support:
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For any queries contact,

Omkar Parkhi: omkar@robots.ox.ac.uk

References:
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[1] O. M. Parkhi, A. Vedaldi, A. Zisserman, C. V. Jawahar
   Cats and Dogs  
   IEEE Conference on Computer Vision and Pattern Recognition, 2012

Note:
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Dataset is made available for research purposes only. Use of these images must respect 
the corresponding terms of use of original websites from which they are taken.
See [1] for list of websites.