Datasets:
File size: 1,869 Bytes
5ce5664 c8464f0 e3f41ff b73dd1b e3f41ff fa9d27b 5ce5664 cf25d1e d4fde75 cf25d1e 6a48ec9 bd5effa daad69a bd5effa 1c09990 c0e9e7b 1c09990 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
---
license: apache-2.0
tags:
- chess
- HCS
- handwriting
- scoresheets
- forms
size_categories:
- n<1K
task_categories:
- image-to-text
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: labels
sequence: string
splits:
- name: train
num_bytes: 359944485.0
num_examples: 206
download_size: 359895992
dataset_size: 359944485.0
---
# Disclaimer
This is not data that I created. It originally came from the Paper [_Digitization of Handwritten Chess Scoresheets with a BiLSTM Network_](https://www.mdpi.com/1477430)
You can also find the dataset [Chesscorner/HCS_Dataset-csv](https://huggingface.co/datasets/Chesscorner/HCS_Dataset-csv), [Chesscorner/HCS_pictures](https://huggingface.co/datasets/Chesscorner/HCS_pictures), [here](https://sites.google.com/view/chess-scoresheet-dataset) and [here](https://tc11.cvc.uab.es/datasets/HCS_1)
# Datasets
There are 2 versions of this dataset
- unprocessed_hcs Dataset where you are right now
- processed_hcs Dataset where the extracted move boxes are provided which can be found [here](https://huggingface.co/datasets/BenjaminKost/processed_hcs)
# Description
The Handwritten Chess Scoresheet Datase (HCS) contains a set of single and double paged chess scoresheet images with ground truth labels.
The unprocessed images are a list of the scoresheets the corresponding labels.
The labels are a list of strings of the chess moves shown on the scoresheet in the order of the right order as on the scoresheet.
# Usage
## In Python script
```python
import datasets
unprocessed_hcs = datasets.load_dataset("Benjaminkost/unprocessed_hcs")
# Show first image
first_image = unprocessed_hcs["train"][0]["image"]
first_label = unprocessed_hcs["train"][0]["labels"]
first_image.show()
print(first_label)
```
|