| --- |
| license: mit |
| language: |
| - km |
| task_categories: |
| - image-to-text |
| tags: |
| - ocr |
| - khmer-ocr |
| - benchmark |
| pretty_name: KHOB (325 lines) |
| size_categories: |
| - n<1K |
| --- |
| |
| # KHOB, 325 text lines |
|
|
| 325 Khmer text-line images with their transcriptions, cropped from the [Khmer OCR Benchmark (KHOB)](https://github.com/EKYCSolutions/khmer-ocr-benchmark-dataset) by EKYC Solutions: scanned Cambodian government documents with clean backgrounds and compression artefacts. One image is one line. |
|
|
| This is the KHOB test set in the [Netra OCR](https://github.com/netra-ai-lab/Netra-OCR) results, where the recognizer scores 0.96% CER with beam search and 1.29% greedy. |
|
|
| | Column | | |
| | --- | --- | |
| | `image` | the line crop | |
| | `label` | its text | |
| | `file_name` | the original crop's name: task, document and line number | |
|
|
| ## Use |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("Netra-Lab/khob-eval", split="train") |
| ``` |
|
|
| With the Netra OCR repository, the `khob` preset scores any model on it: |
|
|
| ```bash |
| bash training/evaluate.sh published --test khob |
| ``` |
|
|
| ## License |
|
|
| MIT, as the original KHOB dataset. Credit: EKYC Solutions, [khmer-ocr-benchmark-dataset](https://github.com/EKYCSolutions/khmer-ocr-benchmark-dataset). |
|
|
