| --- |
| license: mit |
| task_categories: |
| - image-classification |
| - image-to-text |
| - image-feature-extraction |
| tags: |
| - handwriting-recognition |
| - OCR |
| - Marathi |
| - image-processing |
| - deep-learning |
| - computer-vision |
| pretty_name: Marathi Handwritten OCR |
| size_categories: |
| - 1K<n<10K |
| language: |
| - mr |
| --- |
| |
| # Dataset Card for Marathi Handwritten OCR Dataset |
|
|
| ### Dataset Description |
|
|
| - **Repository:** processvenue/Marathi_Handwritten |
| - **Total Examples:** 2520 |
| - **Splits:** |
| - train: 2016 examples |
| - validation: 504 examples |
| - **Features:** image, id, filename, label, type |
| - **Size:** 2520 images |
| - **Language:** mr |
| - **License:** mit |
| |
| ### Dataset Summary |
| |
| The Marathi Handwritten Text Dataset is a collection of handwritten text images in Marathi (देवनागरी लिपी), |
| aimed at supporting the development of Optical Character Recognition (OCR) systems, handwriting analysis tools, |
| and language research.The dataset was curated from native Marathi speakers to ensure a variety of handwriting styles and character variations. |
| The dataset contains 2520 images with two categories: |
| - बाराखडी (Barakhadi/syllables): 560 characters |
| - शब्द (Words): 1949 words |
| - Image Format: PNG |
| - Label Format: Text file |
| - Image Dimensions: 115x57 OR 114x58 pixels |
| - Storage Format: Parquet (Hugging Face) |
| |
| Language Statistics: |
| - Marathi is the third most spoken language in India |
| - Approximately 83 million speakers (7% of India's population) |
| - Official language of Maharashtra |
| - One of the 22 scheduled languages of India |
| |
| Applications |
| 1. OCR Development |
| - Handwriting recognition systems |
| - Document digitization |
| - Text extraction tools |
| |
| 2. Educational Tools |
| - Language learning applications |
| - Writing practice systems |
| - Digital literacy programs |
| |
| 3. Research Applications |
| - Script analysis |
| - Language processing |
| - Pattern recognition studies |
| |
| |
| ### Data Fields |
| |
| - `image`: Image feature (PIL Image) |
| - `id`: Feature field |
| - `filename`: Feature field |
| - `label`: Feature field |
| - `type`: Feature field |
| |
| ### Dataset Creation |
| |
| The dataset was created through careful curation of handwritten samples from native Marathi speakers. |
| The dataset includes both character-level (syllables) and word-level annotations. |
| Contributors were provided with pre-written text designed to capture: |
| - Common character variations |
| - Diverse writing styles |
| - Standard word formations |
| - Typical punctuation usage |
| |
| The images were carefully processed and stored in PNG format, while metadata and labels were structured |
| in a Parquet file format. |
| |
| |
| ### Usage Example |
| |
| ```python |
| from datasets import load_dataset |
| import matplotlib.pyplot as plt |
|
|
| # Load the dataset |
| dataset = load_dataset("processvenue/Marathi_Handwritten") |
|
|
| # Get an example from train split |
| example = dataset['train'][0] |
|
|
| # Display the image |
| plt.figure(figsize=(5, 5)) |
| plt.imshow(example['image']) |
| plt.title(f"Sample Image") |
| plt.axis('off') |
| plt.show() |
| ``` |
| |
| ### Citation |
| |
| If you use this dataset in your research, please cite: |
| |
| ``` |
| @misc{sanskrit-ocr-dataset, |
| title = {Sanskrit OCR Dataset}, |
| author = {ProcessVenue}, |
| year = {2024}, |
| publisher = {HuggingFace}, |
| url = {https://huggingface.co/datasets/processvenue/Sanskrit-OCR-Dataset}, |
| organization = {ProcessVenue}, |
| contact = {sales@processvenue.com}, |
| Website = {https://www.processvenue.com/} |
| } |
| ``` |
| |
| |
| ### References |
| |
| ``` |
| @misc{Sarode_Marathi_Handwritten_Text, |
| author = {Hrushikesh Sarode}, |
| title = {Marathi Handwritten Text Dataset}, |
| year = {n.d.}, |
| url = {https://www.kaggle.com/datasets/hrushikeshsarode/marathi-handwritten-text-dataset}, |
| note = {Accessed: February 12, 2025} |
| } |
| ``` |
