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--- |
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dataset_info: |
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features: |
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- name: id |
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dtype: string |
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- name: image |
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dtype: image |
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- name: text |
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dtype: string |
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- name: file_name |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 1460609496 |
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num_examples: 2213 |
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download_size: 1611806392 |
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dataset_size: 1460609496 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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# KHOB‑LEVEL2 (Scene Text OCR Subset) |
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## Important Attribution (Full Credit) |
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This dataset is a cropped/simplified subset of Level 2: Scene Text Images from the original open‑source project: |
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Khmer OCR Benchmark Dataset — created and maintained by EKYC Solutions and collaborators. |
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- Original GitHub repository: https://github.com/EKYCSolutions/khmer-ocr-benchmark-dataset?tab=readme-ov-file |
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- Official full dataset download (Google Drive): https://drive.google.com/drive/folders/1YczKEIha64Qpjk9Wsbp0-r7PFoYrgvga |
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All credit goes to EKYC Solutions and the original authors. This Hugging Face version is only shared as a convenient subset for quick OCR testing. |
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--- |
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## Background |
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In Cambodia, Khmer Optical Character Recognition (OCR) is an active area of AI development. However, evaluating Khmer OCR engines is difficult because: |
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1. Many OCR systems benchmark only on internal datasets (biased results). |
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2. Some benchmarks rely on synthetic computer‑generated datasets, which do not reflect real‑world images. |
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The Khmer OCR Benchmark Dataset addresses this by providing a standardized benchmark with increasing difficulty levels. |
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--- |
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## Dataset Description |
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This subset is derived from: |
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### Level 2: Scene Text Images |
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Level 2 focuses on Khmer printed text appearing in real‑world scenes. Images were captured using mobile devices (e.g., iPhone 13) and include: |
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- Curved Khmer printed text |
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- Occlusions and noise |
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- Reflections |
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- Varied lighting (bright and low light) |
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- Real‑world backgrounds |
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### What does Level 2 evaluate? |
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OCR models that perform well here can recognize Khmer printed text in uncontrolled real‑world environments. |
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--- |
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## Dataset Format |
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This subset is provided in a simple structure that maps each cropped image to a single text label. |
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| Column | Description | |
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|-------------|-----------------------------------------------| |
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| `image` | Scene text image (Level 2 subset) | |
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| `text` | Ground‑truth transcription | |
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| `file_name` | Original image filename | |
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| `id` | Unique identifier | |
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Example entry: |
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```json |
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{ |
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"image": "LS_10_img_01.png", |
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"text": "ហាមចោលសំរាម" |
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} |
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``` |
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--- |
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## Usage Example |
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```python |
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from datasets import load_dataset |
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# Replace with your dataset repo ID on Hugging Face |
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ds = load_dataset("SoyVitou/KHOB-LEVEL2") |
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print(ds["train"][0]) |
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``` |
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--- |
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## Original Source & License |
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This subset is released in the same open‑source spirit as the original benchmark. For the complete dataset, license details, and full acknowledgments, please refer to the official repository: |
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- https://github.com/EKYCSolutions/khmer-ocr-benchmark-dataset |
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--- |
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## Acknowledgment |
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This benchmark dataset was initiated in collaboration with institutions in Cambodia, including: |
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- EKYC Solutions |
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- Prudential Life Assurance PLC |
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- Paragon International University |
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We are grateful for their contribution to improving Khmer OCR research. |
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Note: This Hugging Face dataset is only a small cropped subset for convenience. For serious benchmarking, please download and use the complete dataset from the original authors. |
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--- |
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## Next Steps |
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If helpful, we can extend this dataset card with: |
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- A BibTeX citation |
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- Additional tags (e.g., `ocr`, `scene-text`, `khmer`) |
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- Train/test split description and data curation notes |
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