Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
parquet
Sub-tasks:
multi-class-image-classification
Languages:
English
Size:
100K - 1M
metadata
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- crowdsourced
license: []
multilinguality:
- monolingual
paperswithcode_id: imagenet
pretty_name: Tiny-ImageNet
size_categories:
- 100K<n<1M
source_datasets:
- extended|imagenet-1k
task_categories:
- image-classification
task_ids:
- multi-class-image-classification
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': n01443537
'1': n01629819
'2': n01641577
'3': n01644900
'4': n01698640
'5': n01742172
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'64': n02788148
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'68': n02802426
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'99': n03250847
'100': n03255030
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'153': n04285008
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'180': n07615774
'181': n07695742
'182': n07711569
'183': n07715103
'184': n07720875
'185': n07734744
'186': n07747607
'187': n07749582
'188': n07753592
'189': n07768694
'190': n07871810
'191': n07873807
'192': n07875152
'193': n07920052
'194': n09193705
'195': n09246464
'196': n09256479
'197': n09332890
'198': n09428293
'199': n12267677
splits:
- name: train
num_bytes: 192793264.38
num_examples: 98179
- name: validation
num_bytes: 9626623.079
num_examples: 4909
- name: test
num_bytes: 9642629.914
num_examples: 4923
download_size: 165987322
dataset_size: 212062517.373
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
Dataset Card for tiny-imagenet-200-clean
Dataset Description
- Homepage: https://www.kaggle.com/c/tiny-imagenet
- Repository: [Needs More Information]
- Paper: http://cs231n.stanford.edu/reports/2017/pdfs/930.pdf
- Leaderboard: https://paperswithcode.com/sota/image-classification-on-tiny-imagenet-1
Dataset Summary
The original Tiny ImageNet contained 100000 images of 200 classes (500 for each class) downsized to 64×64 colored images. Each class has 500 training images, 50 validation images, and 50 test images.
This clean version removed grey scale images and only kept RGB images.
Languages
The class labels in the dataset are in English.
Dataset Structure
Data Instances
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=64x64 at 0x1A800E8E190,
'label': 15
}
Data Fields
- image: A PIL.Image.Image object containing the image.
- label: an int classification label.
Data Splits
| Train | Validation | Test | |
|---|---|---|---|
| # of samples | 98179 | 4909 | 4923 |
Usage
Example
Load Dataset
def example_usage():
tiny_imagenet = load_dataset('slegroux/tiny-imagenet-200-clean', split='train')
print(tiny_imagenet[0])
if __name__ == '__main__':
example_usage()