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---
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",
}
``` |