---
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",
}
```