- Description:
Imagewang contains Imagenette and Imagewoof combined Image网 (pronounced "Imagewang"; 网 means "net" in Chinese) contains Imagenette and Imagewoof combined, but with some twists that make it into a tricky semi-supervised unbalanced classification problem:
- The validation set is the same as Imagewoof (i.e. 30% of Imagewoof images); there are no Imagenette images in the validation set (they're all in the training set)
- Only 10% of Imagewoof images are in the training set!
- The remaining are in the unsup ("unsupervised") directory, and you can not use their labels in training!
- It's even hard to type and hard to say!
The dataset comes in three variants:
- Full size
- 320 px
- 160 px
This dataset consists of the Imagenette dataset {size} variant.
Additional Documentation: Explore on Papers With Code
Config description: Imagewang contains Imagenette and Imagewoof combined.
Homepage: https://github.com/fastai/imagenette
Source code:
tfds.datasets.imagewang.Builder
Versions:
2.0.0
(default): No release notes.
Splits:
Split | Examples |
---|---|
'train' |
14,669 |
'validation' |
3,929 |
- Feature structure:
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=uint8),
'label': ClassLabel(shape=(), dtype=int64, num_classes=20),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
image | Image | (None, None, 3) | uint8 | |
label | ClassLabel | int64 |
Supervised keys (See
as_supervised
doc):('image', 'label')
Citation:
@misc{imagewang,
author = "Jeremy Howard",
title = "Imagewang",
url = "https://github.com/fastai/imagenette/"
}
imagewang/full-size (default config)
Download size:
2.70 GiB
Dataset size:
1.97 GiB
Auto-cached (documentation): No
Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
imagewang/320px
Download size:
638.80 MiB
Dataset size:
460.81 MiB
Auto-cached (documentation): No
Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
imagewang/160px
Download size:
182.63 MiB
Dataset size:
140.40 MiB
Auto-cached (documentation): Yes
Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):