README.md

metadata

language:
  - en
  - vi
license: apache-2.0
size_categories:
  - 10K<n<100K
task_categories:
  - image-to-image
pretty_name: NomGenie - Font Diffusion for Sino-Nom Language
dataset_info:
  - config_name: comparison
    features:
      - name: character
        dtype: string
      - name: style
        dtype: string
      - name: font
        dtype: string
      - name: content_image
        dtype: image
      - name: style_image
        dtype: image
      - name: target_image
        dtype: image
      - name: comparison_image
        dtype: image
      - name: content_hash
        dtype: string
      - name: target_hash
        dtype: string
    splits:
      - name: handwritten_original
        num_bytes: 9235671096
        num_examples: 75512
      - name: handwritten_val
        num_bytes: 125036866
        num_examples: 943
      - name: handwritten_train
        num_bytes: 7186472967
        num_examples: 59472
    download_size: 14752106451
    dataset_size: 16547180929
  - config_name: default
    features:
      - name: character
        dtype: string
      - name: style
        dtype: string
      - name: font
        dtype: string
      - name: content_image
        dtype: image
      - name: target_image
        dtype: image
      - name: content_hash
        dtype: string
      - name: target_hash
        dtype: string
    splits:
      - name: train_original
        num_bytes: 583130879
        num_examples: 41245
      - name: train
        num_bytes: 21425838
        num_examples: 1732
      - name: val
        num_bytes: 1090108
        num_examples: 86
      - name: handwritten_original
        num_bytes: 970527402
        num_examples: 75512
      - name: handwritten_train
        num_bytes: 765653543
        num_examples: 59472
      - name: handwritten_val
        num_bytes: 11967171
        num_examples: 943
    download_size: 30344615849
    dataset_size: 2353794941
  - config_name: streaming
    features:
      - name: character
        dtype: string
      - name: style
        dtype: string
      - name: font
        dtype: string
      - name: content_image
        dtype: image
      - name: style_image
        dtype: image
      - name: target_image
        dtype: image
      - name: comparison_image
        dtype: image
      - name: content_hash
        dtype: string
      - name: target_hash
        dtype: string
    splits:
      - name: train
        num_bytes: 2794896921
        num_examples: 61236
      - name: val
        num_bytes: 33483349
        num_examples: 752
      - name: total
        num_bytes: 3440080525
        num_examples: 75560
    download_size: 36084952999
    dataset_size: 6275047388
configs:
  - config_name: comparison
    data_files:
      - split: handwritten_original
        path: comparison/handwritten_original-*
      - split: handwritten_val
        path: comparison/handwritten_val-*
      - split: handwritten_train
        path: comparison/handwritten_train-*
  - config_name: default
    data_files:
      - split: train_original
        path: data/train_original-*
      - split: train
        path: data/train-*
      - split: val
        path: data/val-*
      - split: handwritten_original
        path: data/handwritten_original-*
      - split: handwritten_train
        path: data/handwritten_train-*
      - split: handwritten_val
        path: data/handwritten_val-*
  - config_name: streaming
    data_files:
      - split: total
        path: streaming/total-*
      - split: val
        path: streaming/val-*
      - split: train
        path: streaming/train-*
tags:
  - font
  - diffusion
  - deep-learning
  - computer-vision

NomGenie: Font Diffusion for Sino-Nom Language

NomGenie is a specialized image-to-image dataset designed for font generation and style transfer within the Sino-Nom (Hán-Nôm) script system. This dataset facilitates the training of deep learning models—particularly Diffusion Models and GANs—to preserve the historical and structural integrity of Vietnamese Nom characters while applying diverse typographic styles.

Dataset Description

The dataset consists of paired images: a content image (representing the skeletal or standard structure of a character) and a target image (representing the character rendered in a specific artistic or historical font style).

Key Features

• character: The specific Sino-Nom character represented.
• style/font: Metadata identifying the aesthetic transformation applied.
• content_image: The source glyph used as the structural reference.
• target_image: The ground truth stylized glyph for model supervision.
• Hashing: content_hash and target_hash are provided to ensure data integrity and assist in deduplication.

Dataset Structure

Data Splits

The dataset is organized into three distinct splits to support various training stages:

Split	Examples	Size	Description
train_original	8,235	124.79 MB	The full original training set.
train	5,172	79.72 MB	A curated subset optimized for standard training.
val	318	4.48 MB	Validation set for hyperparameter tuning and evaluation.

Quick Start

To use this dataset with the Hugging Face datasets library:

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("path/to/NomGenie")

# Access a training sample
sample = dataset['train'][0]
display(sample['content_image'])
display(sample['target_image'])

## Technical Details
- Task Category: image-to-image

- Languages: Vietnamese (vi), English (en)

- License: Apache 2.0

- Primary Use Case: Generative AI for cultural heritage preservation and digital typography.