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README.md
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---
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license: mit
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task_categories:
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- image-classification
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tags: ['handwriting-recognition', 'OCR', 'Marathi', 'image-processing', 'deep-learning', 'computer-vision']
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pretty_name: Marathi Handwritten OCR
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size_categories:
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- 1K<n<10K
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language:
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- mr
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---
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# Dataset Card for Marathi Handwritten OCR Dataset
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### Dataset Description
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- **Repository:** processvenue/Marathi_Handwritten
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- **Total Examples:** 2520
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- **Splits:**
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- train: 2016 examples
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- validation: 504 examples
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- **Features:** image, id, filename, label, type
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- **Size:** 2520 images
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- **Language:** mr
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- **License:** mit
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### Dataset Summary
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The Marathi Handwritten Text Dataset is a collection of handwritten text images in Marathi (देवनागरी लिपी),
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aimed at supporting the development of Optical Character Recognition (OCR) systems, handwriting analysis tools,
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and language research.The dataset was curated from native Marathi speakers to ensure a variety of handwriting styles and character variations.
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The dataset contains 2520 images with two categories:
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- बाराखडी (Barakhadi/syllables): 560 characters
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- शब्द (Words): 1949 words
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- Image Format: PNG
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- Label Format: Text file
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- Image Dimensions: 115x57 OR 114x58 pixels
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- Storage Format: Parquet (Hugging Face)
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Language Statistics:
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- Marathi is the third most spoken language in India
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- Approximately 83 million speakers (7% of India's population)
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- Official language of Maharashtra
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- One of the 22 scheduled languages of India
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Applications
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1. OCR Development
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- Handwriting recognition systems
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- Document digitization
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- Text extraction tools
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2. Educational Tools
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- Language learning applications
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- Writing practice systems
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- Digital literacy programs
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3. Research Applications
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- Script analysis
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- Language processing
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- Pattern recognition studies
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### Data Fields
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- `image`: Image feature (PIL Image)
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- `id`: Feature field
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- `filename`: Feature field
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- `label`: Feature field
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- `type`: Feature field
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### Dataset Creation
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The dataset was created through careful curation of handwritten samples from native Marathi speakers.
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The dataset includes both character-level (syllables) and word-level annotations.
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Contributors were provided with pre-written text designed to capture:
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- Common character variations
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- Diverse writing styles
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- Standard word formations
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- Typical punctuation usage
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The images were carefully processed and stored in PNG format, while metadata and labels were structured
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in a Parquet file format.
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### Usage Example
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```python
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from datasets import load_dataset
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import matplotlib.pyplot as plt
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# Load the dataset
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dataset = load_dataset("processvenue/Marathi_Handwritten")
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# Get an example from train split
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example = dataset['train'][0]
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# Display the image
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plt.figure(figsize=(5, 5))
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plt.imshow(example['image'])
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plt.title(f"Sample Image")
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plt.axis('off')
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plt.show()
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```
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### Citation
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If you use this dataset in your research, please cite:
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```
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@dataset{language_identification_2024,
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author = {ML Technology Team},
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title = {Multilingual Headlines Language Identification Dataset},
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year = {2024},
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publisher = {Hugging Face},
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url = {https://huggingface.co/datasets/MLTechnology/language-identification}
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}
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```
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### References
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```
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@misc{Sarode_Marathi_Handwritten_Text,
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author = {Hrushikesh Sarode},
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title = {Marathi Handwritten Text Dataset},
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year = {n.d.},
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url = {https://www.kaggle.com/datasets/hrushikeshsarode/marathi-handwritten-text-dataset},
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note = {Accessed: February 12, 2025}
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}
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```
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