Missed TensorFlow Dev Summit? Check out the video playlist. Watch recordings

voc

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'image/filename': Text(shape=(), dtype=tf.string),
    'labels': Sequence(ClassLabel(shape=(), dtype=tf.int64, num_classes=20)),
    'labels_no_difficult': Sequence(ClassLabel(shape=(), dtype=tf.int64, num_classes=20)),
    'objects': Sequence({
        'bbox': BBoxFeature(shape=(4,), dtype=tf.float32),
        'is_difficult': tf.bool,
        'is_truncated': tf.bool,
        'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=20),
        'pose': ClassLabel(shape=(), dtype=tf.int64, num_classes=5),
    }),
})

voc/2007 (default config)

  • Description:

This dataset contains the data from the PASCAL Visual Object Classes Challenge 2007, a.k.a. VOC2007, corresponding to the Classification and Detection competitions. A total of 9963 images are included in this dataset, where each image contains a set of objects, out of 20 different classes, making a total of 24640 annotated objects. In the Classification competition, the goal is to predict the set of labels contained in the image, while in the Detection competition the goal is to predict the bounding box and label of each individual object. WARNING: As per the official dataset, the test set of VOC2012 does not contain annotations.

  • Config description: This dataset contains the data from the PASCAL Visual Object Classes Challenge 2007, a.k.a. VOC2007, corresponding to the Classification and Detection competitions. A total of 9963 images are included in this dataset, where each image contains a set of objects, out of 20 different classes, making a total of 24640 annotated objects. In the Classification competition, the goal is to predict the set of labels contained in the image, while in the Detection competition the goal is to predict the bounding box and label of each individual object. WARNING: As per the official dataset, the test set of VOC2012 does not contain annotations.
  • Homepage: http://host.robots.ox.ac.uk/pascal/VOC/voc2007/
  • Download size: 868.85 MiB
  • Splits:
Split Examples
'test' 4,952
'train' 2,501
'validation' 2,510
  • Citation:
@misc{pascal-voc-2007,
    author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
    title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2007 {(VOC2007)} {R}esults",
    howpublished = "http://www.pascal-network.org/challenges/VOC/voc2007/workshop/index.html"}

voc/2012

  • Description:

This dataset contains the data from the PASCAL Visual Object Classes Challenge 2012, a.k.a. VOC2012, corresponding to the Classification and Detection competitions. A total of 11540 images are included in this dataset, where each image contains a set of objects, out of 20 different classes, making a total of 27450 annotated objects. In the Classification competition, the goal is to predict the set of labels contained in the image, while in the Detection competition the goal is to predict the bounding box and label of each individual object. WARNING: As per the official dataset, the test set of VOC2012 does not contain annotations.

  • Config description: This dataset contains the data from the PASCAL Visual Object Classes Challenge 2012, a.k.a. VOC2012, corresponding to the Classification and Detection competitions. A total of 11540 images are included in this dataset, where each image contains a set of objects, out of 20 different classes, making a total of 27450 annotated objects. In the Classification competition, the goal is to predict the set of labels contained in the image, while in the Detection competition the goal is to predict the bounding box and label of each individual object. WARNING: As per the official dataset, the test set of VOC2012 does not contain annotations.
  • Homepage: http://host.robots.ox.ac.uk/pascal/VOC/voc2012/
  • Download size: 3.59 GiB
  • Splits:
Split Examples
'test' 10,991
'train' 5,717
'validation' 5,823
  • Citation:
@misc{pascal-voc-2012,
    author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
    title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2012 {(VOC2012)} {R}esults",
    howpublished = "http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html"}