datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
intel-image-classification
Intel Image Classification
The Intel Image Classification dataset contains images of natural scenes categorized into six classes:
Buildings
Forest
Glacier
Mountain
Sea
Street
📆 Content
The dataset contains ~25,000 images of size 150x150 pixels.
Images are evenly distributed across 6 categories:
{'buildings' -> 0,
'forest' -> 1,
'glacier' -> 2,
'mountain' -> 3,
'sea' -> 4,
'street' -> 5 }
It is divided into three parts:
Training set: ~14… See the full description on the dataset page: https://huggingface.co/datasets/sfarrukhm/intel-image-classification.autotrain-data-image-classification
AutoTrain Dataset for project: image-classification
Dataset Description
This dataset has been automatically processed by AutoTrain for project image-classification.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<79x80 RGBA PIL image>",
"target": 1
},
{
"image": "<547x108 RGBA PIL image>",
"target": 1
}]… See the full description on the dataset page: https://huggingface.co/datasets/fsuarez/autotrain-data-image-classification.Afrivoice_Kinyarwanda_Image_Domain_classification
Dataset Description
This dataset is a restructured version of Afrivoice Kinyarwanda, reorganized for image domain classification. The original audio-and-image manifest data was regrouped into a standard Hugging Face imagefolder layout (train/validation/test splits, one subfolder per class) so it can be loaded directly with datasets.load_dataset("imagefolder", ...) for training image classifiers.
No new images were collected and no image content was modified beyond format… See the full description on the dataset page: https://huggingface.co/datasets/Kira-Floris/Afrivoice_Kinyarwanda_Image_Domain_classification.Animal_Image_Classification_DatasetDataset Summary:
The Animal Image Classification Dataset is a comprehensive collection of images tailored for the development and evaluation of machine learning models in the field of computer vision. It contains 3,000 JPG images, carefully segmented into three classes representing common pets and wildlife: cats, dogs, and snakes.
Dataset Contents:
cats/: A set of 1,000 JPG images of cats, showcasing a wide array of breeds, environments, and postures.
dogs/: A diverse compilation of 1,000 dog… See the full description on the dataset page: https://huggingface.co/datasets/AlvaroVasquezAI/Animal_Image_Classification_Dataset.japanese-image-classification-evaluation-dataset
recruit-jp/japanese-image-classification-evaluation-dataset
Overview
Developed by: Recruit Co., Ltd.
Dataset type: Image Classification
Language(s): Japanese
LICENSE: CC-BY-4.0
More details are described in our tech blog post.
日本語CLIP学習済みモデルとその評価用データセットの公開
Dataset Details
This dataset is comprised of four image classification tasks related to concepts and things unique to Japan. Specifically, is consists of the following tasks.
jafood101: Image… See the full description on the dataset page: https://huggingface.co/datasets/recruit-jp/japanese-image-classification-evaluation-dataset.pokemon_card_image_for_authenticity_classification
Pokemon Card Image for Authenticity Classification
This dataset contains front/back images of Pokemon cards for authenticity experiments.
Dataset structure
Images/: all image files (.jpeg)
Images/metadata.jsonl: metadata used by Hugging Face imagefolder
labels.csv: flat label file with the same rows as metadata
Columns
image: image object loaded from file
id: image filename (unique id)
side: card side (0 = front, 1 = back)
labels: authenticity label (1 =… See the full description on the dataset page: https://huggingface.co/datasets/stevelohwc/pokemon_card_image_for_authenticity_classification.fast_food_image_classificationProduct_Image_Classification
Product Image Classification Dataset
Датасет изображений товаров, собранный с крупных узбекских маркетплейсов (asaxiy.uz, texnomart.uz, olcha.uz) для задачи автоматической классификации e-commerce продукции.
Описание датасета
Данный набор данных содержит фотографии товаров, разбитых по 5 основным категориям электроники. Данные прошли автоматическую очистку от поврежденных файлов и дедупликацию по MD5-хешу.
Категории (Classes):
headphones — Наушники… See the full description on the dataset page: https://huggingface.co/datasets/NurzatS/Product_Image_Classification.garbage-image-classification-detection
Garbage Image dataset
Dataset consists of images, bounding-boxes and segmentations for each elements.
@misc{
garbage-classifier-oehkt_dataset,
title = { Garbage Classifier Dataset },
type = { Open Source Dataset },
author = { Student },
howpublished = { \url{ https://universe.roboflow.com/student-utr07/garbage-classifier-oehkt } },
url = { https://universe.roboflow.com/student-utr07/garbage-classifier-oehkt },
journal = { Roboflow Universe },
publisher = { Roboflow… See the full description on the dataset page: https://huggingface.co/datasets/dmedhi/garbage-image-classification-detection.Matthiola-incana-Leaf-Image-Classification
Matthiola incana Leaf Image Classification dataset
Matthiola incana Leaf Image Classification(MiLIC) dataset is intended to create a model for classifying images of Matthiola incana leaves into single-flowered leaf or double-flowered leaf.
Matthiola incana
Matthiola incana, a member of the family Brassicaceae, is an ornamental plant cultivated worldwide for its beautiful flowers. This species exhibits two flower forms: single and double flowers. The market for… See the full description on the dataset page: https://huggingface.co/datasets/Kentaro-Machida/Matthiola-incana-Leaf-Image-Classification.autotrain-data-animal-image-classification
AutoTrain Dataset for project: animal-image-classification
Dataset Description
This dataset has been automatically processed by AutoTrain for project animal-image-classification.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<366x274 RGB PIL image>",
"target": 0
},
{
"image": "<367x274 RGB PIL image>",
"target":… See the full description on the dataset page: https://huggingface.co/datasets/BalajiAIdev/autotrain-data-animal-image-classification.front_image_classification
Front image classification dataset
This dataset contains Open Food Facts images, each assigned with one of the two following classes:
front (ID 0)
other (ID 1)
Front images are the "default" image of a product, displayed on Open Food Facts product page. A front image is most of the time a photo of the front side of the product packaging. It's useful to be able to detect front images so that we can update the front image with a newer version (when the packaging changes for… See the full description on the dataset page: https://huggingface.co/datasets/openfoodfacts/front_image_classification.autotrain-data-histopathological_image_classification
AutoTrain Dataset for project: histopathological_image_classification
Dataset Description
This dataset has been automatically processed by AutoTrain for project histopathological_image_classification.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<700x460 RGB PIL image>",
"target": 6
},
{
"image": "<700x460 RGB PIL… See the full description on the dataset page: https://huggingface.co/datasets/JoffreyMa/autotrain-data-histopathological_image_classification.animal_image_classificationAnimal_Image_Classification_DatasetDataset Summary:
The Animal Image Classification Dataset is a comprehensive collection of images tailored for the development and evaluation of machine learning models in the field of computer vision. It contains 3,000 JPG images, carefully segmented into three classes representing common pets and wildlife: cats, dogs, and snakes.
Dataset Contents:
cats/: A set of 1,000 JPG images of cats, showcasing a wide array of breeds, environments, and postures.
dogs/: A diverse compilation of 1,000 dog… See the full description on the dataset page: https://huggingface.co/datasets/Jogitha/Animal_Image_Classification_Dataset.autotrain-data-image-classification
AutoTrain Dataset for project: image-classification
Dataset Description
This dataset has been automatically processed by AutoTrain for project image-classification.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<500x333 RGB PIL image>",
"target": 0
},
{
"image": "<320x240 RGB PIL image>",
"target": 4
}]… See the full description on the dataset page: https://huggingface.co/datasets/Cuplex/autotrain-data-image-classification.Tom_and_Jerry_Image_Classification
Tom and Jerry Image Classification
Dataset Summary
The "Tom and Jerry Image Classification" dataset [1] has 5,478 images. These are classified as:
images with only "Tom": tom
images with only "Jerry": jerry
images with both "Tom" and "Jerry": tom_jerry_1
images without either character: tom_jerry_0
Supported Tasks and Leaderboards
Token Classification (Note: If this is image classification, consider changing this to image-classification in the YAML metadata… See the full description on the dataset page: https://huggingface.co/datasets/svav18/Tom_and_Jerry_Image_Classification.image-classification-100-classesThis dataset was used to train image classification models.
There are 100 classes
Each class has 10 images.
Classes are labeled from 0 to 99
Images belonging to a class are found inside that class' directory.
image_classification
Visualization of Image Classification Task Cases Samples
Check dataset samples visualization by viewing Dataset Viewer.
The sampling procedure is guided by the Elo distribution introduced in our method.
Original dataset is validation set of ImageNet.
samples/origin: 4998/50000
License
This repository is licensed under the Apache License 2.0
animal_image_classificationedgeimpulse-test-image-classification
Edgeimpulse Test Image Classification
This dataset is an integration-test fixture for Edge Impulse's "Import from Hugging Face" flow.
Structure
Splits: train, validation, test
Main fields: image, label
Extra metadata columns (from metadata.csv):
source_split
source_file
source_stem
source_path
Important note
Label source mode: source-metadata.
autotrain-data-satellite-image-classification
AutoTrain Dataset for project: satellite-image-classification
Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project satellite-image-classification.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<256x256 CMYK PIL image>",
"target": 0
},
{
"image": "<256x256 CMYK PIL image>"… See the full description on the dataset page: https://huggingface.co/datasets/lky23/autotrain-data-satellite-image-classification.autotrain-data-satellite-image-classification
AutoTrain Dataset for project: satellite-image-classification
Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project satellite-image-classification.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<256x256 CMYK PIL image>",
"target": 0
},
{
"image": "<256x256 CMYK PIL image>"… See the full description on the dataset page: https://huggingface.co/datasets/jhyeok724/autotrain-data-satellite-image-classification.