- Description:
Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed. MIT Scene Parsing Benchmark (SceneParse150) provides a standard training and evaluation platform for the algorithms of scene parsing.
Homepage: http://sceneparsing.csail.mit.edu/
Source code:
tfds.image.SceneParse150
Versions:
1.0.0
(default): No release notes.
Download size:
936.97 MiB
Dataset size:
Unknown size
Auto-cached (documentation): Unknown
Splits:
Split | Examples |
---|---|
'test' |
2,000 |
'train' |
20,210 |
- Features:
FeaturesDict({
'annotation': Image(shape=(None, None, 3), dtype=tf.uint8),
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
})
Supervised keys (See
as_supervised
doc):('image', 'annotation')
Citation:
@inproceedings{zhou2017scene,
title={Scene Parsing through ADE20K Dataset},
author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
year={2017}
}
Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):