metadata
dataset_info:
features:
- name: image
dtype: image
- name: is_document
dtype:
class_label:
names:
'0': 'no'
'1': 'yes'
splits:
- name: train
num_bytes: 4056718648.905889
num_examples: 12810
- name: test
num_bytes: 507010660.1794167
num_examples: 1601
- name: validation
num_bytes: 507327343.9146943
num_examples: 1602
download_size: 5070652743
dataset_size: 5071056653
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
license: other
The DocOrNot dataset contains 50% of images that are pictures, and 50% that are documents.
It was built using 8k images from each one of these sources:
- RVL CDIP (Small) - https://www.kaggle.com/datasets/uditamin/rvl-cdip-small - license: https://www.industrydocuments.ucsf.edu/help/copyright/
- Flickr8k - https://www.kaggle.com/datasets/adityajn105/flickr8k - license: https://creativecommons.org/publicdomain/zero/1.0/
It can be used to train a model and classify an image as being a picture or a document.
Source code used to generate this dataset : https://github.com/tarekziade/docornot