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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.
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