README.md

metadata

dataset_info:
  - config_name: test
    features:
      - name: image
        dtype: image
      - name: code_caption
        dtype: string
    splits:
      - name: train
        num_bytes: 142134244.412
        num_examples: 1188
    download_size: 124563800
    dataset_size: 142134244.412
  - config_name: train
    features:
      - name: image
        dtype: image
      - name: code_caption
        dtype: string
    splits:
      - name: train
        num_bytes: 946697073.77
        num_examples: 10102
    download_size: 853815350
    dataset_size: 946697073.77
  - config_name: validation
    features:
      - name: image
        dtype: image
      - name: code_caption
        dtype: string
    splits:
      - name: train
        num_bytes: 95790792
        num_examples: 594
    download_size: 73916515
    dataset_size: 95790792
configs:
  - config_name: test
    data_files:
      - split: train
        path: test/train-*
  - config_name: train
    data_files:
      - split: train
        path: train/train-*
  - config_name: validation
    data_files:
      - split: train
        path: validation/train-*
task_categories:
  - image-to-image
tags:
  - code
pretty_name: FloCo
size_categories:
  - 10K<n<100K

FloCo Dataset

From: https://vl2g.github.io/projects/floco/

We introduce a new large-scale dataset called "FloCo" for Flowchart images to Python Codes conversion. It contains 11,884 paired flowchart-code samples. Please refer to the paper for more details regarding statistics and dataset construction.

@inproceedings{shukla2023floco,
  author    = "Shukla, Shreya and 
              Gatti, Prajwal and 
              Kumar, Yogesh and
              Yadav, Vikash and
              Mishra, Anand",
  title     = "Towards Making Flowchart Images Machine Interpretable",
  booktitle = "ICDAR",
  year      = "2023",
}