Datasets:

blue7012
/

UIT_HWDB

license: cc-by-4.0
task_categories:
  - image-to-text
  - optical-character-recognition
language:
  - vi
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*-of-*.parquet
      - split: test
        path: data/test-*-of-*.parquet

UIT_HWDB - Vietnamese Handwritten Text Dataset

Dataset Description

UIT_HWDB is a comprehensive dataset for Vietnamese handwritten text recognition. This version combines both line-level and paragraph-level handwriting samples.

Each sample contains:

A handwritten text image (line or paragraph)
Ground truth transcription in Vietnamese
Writer identification
Unique image identifier

Dataset Structure

Data Instances

Each instance contains:

image: A PIL Image of the handwritten text
text: The ground truth transcription in Vietnamese
writer_id: Unique identifier for the writer
image_id: Unique identifier for the image

Data Splits

Split	Samples	Writers	Shards
train	8,141	249	8
test	232	6	1
Total	8,373	255	9

Usage

Basic Loading

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("YOUR_USERNAME/UIT_HWDB")

# Access samples
for sample in dataset['train']:
    image = sample['image']      # PIL Image
    text = sample['text']        # Vietnamese text
    writer_id = sample['writer_id']
    image_id = sample['image_id']

Parallel Loading (Recommended for Large Datasets)

# Use multiple workers for faster loading
dataset = load_dataset("YOUR_USERNAME/UIT_HWDB", num_proc=8)

Streaming (For Limited Memory)

# Stream data without downloading entire dataset
dataset = load_dataset("YOUR_USERNAME/UIT_HWDB", streaming=True)

for sample in dataset['train']:
    # Process one sample at a time
    pass

Use in Training

from torch.utils.data import DataLoader

# Convert to PyTorch format
dataset = dataset.with_format("torch")

# Create DataLoader
train_loader = DataLoader(
    dataset['train'],
    batch_size=32,
    shuffle=True,
    num_workers=4
)

for batch in train_loader:
    images = batch['image']
    texts = batch['text']
    # Your training code here...

Dataset Creation

This dataset was converted to Parquet format following HuggingFace best practices:

✅ Sharded into ~450MB chunks for optimal performance
✅ Memory-efficient streaming conversion process
✅ Proper image encoding using HuggingFace Image feature
✅ Compatible with HuggingFace Dataset Viewer
✅ Supports parallel loading and streaming

Citation

If you use this dataset, please cite the original UIT_HWDB paper:

@inproceedings{uitHWDB,
  title={Vietnamese Handwriting Database (UIT-HWDB)},
  author={Your Authors Here},
  booktitle={Conference Name},
  year={Year},
  organization={Organization}
}

License

This dataset is released under CC-BY-4.0 license.