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---
license: apache-2.0
task_categories:
- image-to-text
language:
- gu
tags:
- handwritten-text-recognition
- htr
- gujarati
- ocr
- iiit-indic-hw-words
pretty_name: Gujarati Handwritten Dataset (IIIT-INDIC-HW-WORDS)
size_categories:
- 10K-100K
dataset_info:
features:
- name: file_name
dtype: string
- name: text
dtype: string
- name: image
dtype: image
splits:
- name: train
num_bytes: 2867138581.533
num_examples: 82563
- name: val
num_bytes: 632023288.427
num_examples: 17643
- name: test
num_bytes: 597646751.57
num_examples: 16490
download_size: 4016768714
dataset_size: 4096808621.53
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
- split: test
path: data/test-*
---
# Gujarati Handwritten Word Dataset
This dataset is a subset of the **IIIT-INDIC-HW-WORDS** collection, specifically focused on the **Gujarati** language. It is designed for training and evaluating **Handwritten Text Recognition (HTR)** models.
## Dataset Summary
The original [IIIT-INDIC-HW-WORDS](https://cvit.iiit.ac.in/usodi/istr.php) is a large-scale benchmark for Indic scripts. This Gujarati subset contains word-level images manually written by multiple annotators to capture natural variations in handwriting styles.
### Key Statistics
| Feature | Count |
| :--- | :--- |
| **Total Word Images** | 82,563 |
| **Train Set** | 48,430 |
| **Validation Set** | 17,643 |
| **Test Set** | 16,490 |
---
## Dataset Structure & Extraction
The dataset consists of image folders and corresponding annotation text files. Follow these instructions to map images to their transcriptions:
### 1. Files Overview
* **Images:** Located in the `train/`, `val/`, and `test/` folders.
* **Labels:** Provided in `train.txt`, `val.txt`, and `test.txt`.
* **Lexicon:** `vocab.txt` contains the full list of Unicode strings used in the dataset.
### 2. Label Format
Each row in the label files (`train.txt`, `val.txt`, `test.txt`) follows this format:
` <FileName>, <VocabId> `
### 3. Mapping Logic
The `<VocabId>` is a **0-indexed** pointer to the line number in `vocab.txt`.
* **Step 1:** Locate the `VocabId` for an image in the split text file.
* **Step 2:** Go to that specific line number in `vocab.txt` to extract the Unicode Gujarati string.
---
## Citation
If you use this dataset in your research, please cite the following paper:
```bibtex
@inproceedings{gongidi2021iiit,
title={IIIT-Indic-HW-Words: A Dataset for Indic Handwritten Text Recognition},
author={Gongidi, Santhoshini and Jawahar, CV},
booktitle={Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR)},
pages={444--459},
year={2021},
organization={Springer}
}
```