CLEVR is a diagnostic dataset that tests a range of visual reasoning abilities. It contains minimal biases and has detailed annotations describing the kind of reasoning each question requires.
- URL: https://cs.stanford.edu/people/jcjohns/clevr/
DatasetBuilder
:tfds.image.clevr.CLEVR
- Version:
v1.0.0
Versions:
1.0.0
(default):3.0.0
: New split API (https://tensorflow.org/datasets/splits)
Size:
17.72 GiB
Features
FeaturesDict({
'file_name': Text(shape=(), dtype=tf.string),
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'objects': Sequence({
'3d_coords': Tensor(shape=(3,), dtype=tf.float32),
'color': ClassLabel(shape=(), dtype=tf.int64, num_classes=8),
'material': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
'pixel_coords': Tensor(shape=(3,), dtype=tf.float32),
'rotation': Tensor(shape=(), dtype=tf.float32),
'shape': ClassLabel(shape=(), dtype=tf.int64, num_classes=3),
'size': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
}),
})
Statistics
Split | Examples |
---|---|
ALL | 100,000 |
TRAIN | 70,000 |
TEST | 15,000 |
VALIDATION | 15,000 |
Homepage
Citation
@inproceedings{johnson2017clevr,
title={ {CLEVR}: A diagnostic dataset for compositional language and elementary visual reasoning},
author={Johnson, Justin and Hariharan, Bharath and van der Maaten, Laurens and Fei-Fei, Li and Lawrence Zitnick, C and Girshick, Ross},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
year={2017}
}