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---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': letter
          '1': form
          '2': email
          '3': handwritten
          '4': advertisement
          '5': scientific report
          '6': scientific publication
          '7': specification
          '8': file folder
          '9': news article
          '10': budget
          '11': invoice
          '12': presentation
          '13': questionnaire
          '14': resume
          '15': memo
  splits:
  - name: train
    num_bytes: 978826386
    num_examples: 8000
  - name: test
    num_bytes: 124139952
    num_examples: 992
  download_size: 1039947220
  dataset_size: 1102966338
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
task_categories:
- image-classification
- image-text-to-text
language:
- en
pretty_name: Ryerson Vision Lab Complex Document Information Processing)
size_categories:
- 1K<n<10K
---

# rvl-cdip-document-classification

This dataset is created from original [aharley/rvl_cdip](https://huggingface.co/datasets/aharley/rvl_cdip) dataset using [this notebook](https://colab.research.google.com/drive/1CuER4BrT8uQj0nlPX0Fcek_zYqyaOvGA?usp=sharing)

## Dataset Summary

This dataset consists of 8992 grayscale images in 16 classes, with 562 images per class. 
There are 8000 training images(500 image per class) and 992 test images(62 images per class). 
The images are sized so their largest dimension does not exceed 1000 pixels.