imagewang
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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:
This dataset consists of the Imagenette dataset {size} variant.
Split |
Examples |
'train' |
14,669 |
'validation' |
3,929 |
FeaturesDict({
'image': Image(shape=(None, None, 3), dtype=uint8),
'label': ClassLabel(shape=(), dtype=int64, num_classes=20),
})
Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
image |
Image |
(None, None, 3) |
uint8 |
|
label |
ClassLabel |
|
int64 |
|
@misc{imagewang,
author = "Jeremy Howard",
title = "Imagewang",
url = "https://github.com/fastai/imagenette/"
}
imagewang/full-size (default config)

imagewang/320px

imagewang/160px

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Last updated 2024-06-01 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-06-01 UTC."],[],[],null,["# imagewang\n\n\u003cbr /\u003e\n\n- **Description**:\n\nImagewang contains Imagenette and Imagewoof combined Image网 (pronounced\n\"Imagewang\"; 网 means \"net\" in Chinese) contains Imagenette and Imagewoof\ncombined, but with some twists that make it into a tricky semi-supervised\nunbalanced classification problem:\n\n- 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)\n- Only 10% of Imagewoof images are in the training set!\n- The remaining are in the unsup (\"unsupervised\") directory, and you can not use their labels in training!\n- It's even hard to type and hard to say!\n\nThe dataset comes in three variants:\n\n- Full size\n- 320 px\n- 160 px\n\nThis dataset consists of the Imagenette dataset {size} variant.\n\n- **Additional Documentation** :\n [Explore on Papers With Code\n north_east](https://paperswithcode.com/dataset/imagewang)\n\n- **Config description**: Imagewang contains Imagenette and Imagewoof\n combined.\n\n- **Homepage** :\n \u003chttps://github.com/fastai/imagenette\u003e\n\n- **Source code** :\n [`tfds.datasets.imagewang.Builder`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/datasets/imagewang/imagewang_dataset_builder.py)\n\n- **Versions**:\n\n - **`2.0.0`** (default): No release notes.\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'train'` | 14,669 |\n| `'validation'` | 3,929 |\n\n- **Feature structure**:\n\n FeaturesDict({\n 'image': Image(shape=(None, None, 3), dtype=uint8),\n 'label': ClassLabel(shape=(), dtype=int64, num_classes=20),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|---------|--------------|-----------------|-------|-------------|\n| | FeaturesDict | | | |\n| image | Image | (None, None, 3) | uint8 | |\n| label | ClassLabel | | int64 | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `('image', 'label')`\n\n- **Citation**:\n\n @misc{imagewang,\n author = \"Jeremy Howard\",\n title = \"Imagewang\",\n url = \"https://github.com/fastai/imagenette/\"\n }\n\nimagewang/full-size (default config)\n------------------------------------\n\n- **Download size** : `2.70 GiB`\n\n- **Dataset size** : `1.97 GiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n No\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nimagewang/320px\n---------------\n\n- **Download size** : `638.80 MiB`\n\n- **Dataset size** : `460.81 MiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n No\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nimagewang/160px\n---------------\n\n- **Download size** : `182.63 MiB`\n\n- **Dataset size** : `140.40 MiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n Yes\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples..."]]