metadata
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 8961757
num_examples: 4
download_size: 8964031
dataset_size: 8961757
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Example Dataset for Surya OCR Finetuning
This dataset is an example that lays out the expected format for finetuning Surya OCR.
Data Requirements
Image column: The input images (full pages, blocks, or single text lines — mix freely).
Text column: The transcription corresponding to each image.
For math content, ensure <math display="inline"></math> or <math display="block"></math> tags are wrapped around the latex
Surya OCR supports:
Various aspect ratios
Different image types and qualities
Full-page documents
Cropped blocks of text
Single-line snippets
The base surya model is trained on a wide range of samples from all these categories, and you can combine any of these types in your training dataset for more robust performance, as demonstrated in this example dataset.