SoyVitou/KHOB-LEVEL2
KHOB‑LEVEL2 (Scene Text OCR Subset) Important Attribution (Full Credit) This dataset is a cropped/simplified subset of Level 2: Scene Text Images from the original open‑source project: Khmer OCR Benchmark Dataset — created and maintained by EKYC Solutions and collaborators. Original GitHub repository: https://github.com/EKYCSolutions/khmer-ocr-benchmark-dataset?tab=readme-ov-file Official full dataset download (Google Drive):… See the full description on the dataset page: https://huggingface.co/datasets/SoyVitou/KHOB-LEVEL2.
KHOB‑LEVEL2 (Scene Text OCR Subset)
Important Attribution (Full Credit)
This dataset is a cropped/simplified subset of Level 2: Scene Text Images from the original open‑source project:
Khmer OCR Benchmark Dataset — created and maintained by EKYC Solutions and collaborators.
- Original GitHub repository: https://github.com/EKYCSolutions/khmer-ocr-benchmark-dataset?tab=readme-ov-file
- Official full dataset download (Google Drive): https://drive.google.com/drive/folders/1YczKEIha64Qpjk9Wsbp0-r7PFoYrgvga
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.
Background
In Cambodia, Khmer Optical Character Recognition (OCR) is an active area of AI development. However, evaluating Khmer OCR engines is difficult because:
- Many OCR systems benchmark only on internal datasets (biased results).
- Some benchmarks rely on synthetic computer‑generated datasets, which do not reflect real‑world images.
The Khmer OCR Benchmark Dataset addresses this by providing a standardized benchmark with increasing difficulty levels.
Dataset Description
This subset is derived from:
Level 2: Scene Text Images
Level 2 focuses on Khmer printed text appearing in real‑world scenes. Images were captured using mobile devices (e.g., iPhone 13) and include:
- Curved Khmer printed text
- Occlusions and noise
- Reflections
- Varied lighting (bright and low light)
- Real‑world backgrounds
What does Level 2 evaluate?
OCR models that perform well here can recognize Khmer printed text in uncontrolled real‑world environments.
Dataset Format
This subset is provided in a simple structure that maps each cropped image to a single text label.
Example entry:
{
"image": "LS_10_img_01.png",
"text": "ហាមចោលសំរាម"
}Usage Example
from datasets import load_dataset
# Replace with your dataset repo ID on Hugging Face
ds = load_dataset("SoyVitou/KHOB-LEVEL2")
print(ds["train"][0])Original Source & License
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:
- https://github.com/EKYCSolutions/khmer-ocr-benchmark-dataset
Acknowledgment
This benchmark dataset was initiated in collaboration with institutions in Cambodia, including:
- EKYC Solutions
- Prudential Life Assurance PLC
- Paragon International University
We are grateful for their contribution to improving Khmer OCR research.
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.
Next Steps
If helpful, we can extend this dataset card with:
- A BibTeX citation
- Additional tags (e.g.,
ocr,scene-text,khmer) - Train/test split description and data curation notes
