datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
quickdraw
Dataset Card for Quick, Draw!
This is a processed version of Google's Quick, Draw dataset to be compatible with the latest versions of 🤗 Datasets that support .parquet files. NOTE: this dataset only contains the "preprocessed_bitmaps" subset of the original dataset.
quickdrawThe Quick Draw Dataset is a collection of 50 million drawings across 345 categories, contributed by players of the game Quick, Draw!.
The drawings were captured as timestamped vectors, tagged with metadata including what the player was asked to draw and in which country the player was located.quickdraw-mnist
QuickDraw-MNIST
QuickDraw-MNIST is a 20-class sketch-recognition dataset prepared for Texas A&M's CSCE 624 (Sketch Recognition) class.
The data is sourced from Google's Quick, Draw! dataset.
Dataset Structure
Number of images: 100,000
Number of classes: 20
Images: 64 x 64 grayscale
Labels: integer class ids with a human-readable label_name column
Classes: The Eiffel Tower, airplane, angel, bed, chair, clock, diamond, donut, fork, frog, hourglass, leaf, line, mushroom… See the full description on the dataset page: https://huggingface.co/datasets/oriyonay/quickdraw-mnist.quickdraw-26-classes
Quick! Draw 26 Class Dataset
This dataset is derived from the Google Quick! Draw dataset and contains 26 classes of doodle images drawn by users. The classes include common objects and entities like animals, vehicles, food items, and everyday objects.
Dataset Details
Number of Classes: 26
Total Images: 520,000 (416,000 train, 52,000 val, 52,000 test)
Image Format: PNG images of size 28x28 pixels (grayscale)
Data Fields:
image: PIL Image object
label: Integer label… See the full description on the dataset page: https://huggingface.co/datasets/OmAlve/quickdraw-26-classes.