image imagewidth (px) 1.77k 3.39k | file_name stringlengths 62 67 | markdown stringlengths 416 4.57k | surya_blocks stringlengths 4.76k 205k | inference_info stringclasses 1
value |
|---|---|---|---|---|
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_025.png | <table border="1">
<thead>
<tr>
<th rowspan="2">Ministry/Agency</th>
<th colspan="4">Total Planned Expenditure</th>
<th colspan="5">Committed Funds</th>
<th colspan="4">Additional Funds Required</th>
</tr>
<tr>
<th>2021</th>
<th>2022</th>
<th>2023</th>
<th>Total<br/>2021-2023</th>
<th>Source of<br/>Funds</th>
<th>2021<... | [{"rows": [{"polygon": [[0.0, 0.0], [3387.0, 0.0], [3387.0, 81.488], [0.0, 81.488]], "confidence": null, "row_id": 0, "bbox": [0.0, 0.0, 3387.0, 81.488]}, {"polygon": [[0.0, 81.488], [3387.0, 81.488], [3387.0, 194.45999999999998], [0.0, 194.45999999999998]], "confidence": null, "row_id": 1, "bbox": [0.0, 81.488, 3387.0... | [{"model": "datalab-to/surya-ocr-2", "model_name": "surya-ocr-2", "column_name": "markdown", "blocks_column": "surya_blocks", "task": "table", "table_mode": "full", "backend": "vllm-offline", "page_range": null, "error_rate": 0.0, "timestamp": "2026-08-07T06:57:03.371859+00:00", "script": "surya-ocr.py"}] | |
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_026.png | "<table border=\"1\">\n<thead>\n<tr>\n<th rowspan=\"2\">Ministry/Agency</th>\n<th colspan=\"4\">Tota(...TRUNCATED) | "[{\"rows\": [{\"polygon\": [[3.39, 3.696], [3386.61, 3.696], [3386.61, 81.312], [3.39, 81.312]], \"(...TRUNCATED) | "[{\"model\": \"datalab-to/surya-ocr-2\", \"model_name\": \"surya-ocr-2\", \"column_name\": \"markdo(...TRUNCATED) | |
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_027.png | "<table border=\"1\">\n<thead>\n<tr>\n<th rowspan=\"2\">Ministry/Agency</th>\n<th colspan=\"4\">Tota(...TRUNCATED) | "[{\"rows\": [{\"polygon\": [[3.388, 3.674], [3384.612, 3.674], [3384.612, 80.82799999999999], [3.38(...TRUNCATED) | "[{\"model\": \"datalab-to/surya-ocr-2\", \"model_name\": \"surya-ocr-2\", \"column_name\": \"markdo(...TRUNCATED) | |
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_028.png | "<table border=\"1\">\n<thead>\n<tr>\n<th rowspan=\"2\">Ministry/Agency</th>\n<th colspan=\"4\">Tota(...TRUNCATED) | "[{\"rows\": [{\"polygon\": [[0.0, 0.0], [3390.0, 0.0], [3390.0, 79.378], [0.0, 79.378]], \"confiden(...TRUNCATED) | "[{\"model\": \"datalab-to/surya-ocr-2\", \"model_name\": \"surya-ocr-2\", \"column_name\": \"markdo(...TRUNCATED) | |
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_029.png | "<table border=\"1\">\n<thead>\n<tr>\n<th rowspan=\"2\">Ministry/Agency</th>\n<th colspan=\"4\">Tota(...TRUNCATED) | "[{\"rows\": [{\"polygon\": [[3.3890000000000002, 3.694], [3385.611, 3.694], [3385.611, 79.420999999(...TRUNCATED) | "[{\"model\": \"datalab-to/surya-ocr-2\", \"model_name\": \"surya-ocr-2\", \"column_name\": \"markdo(...TRUNCATED) | |
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_030.png | "<table border=\"1\">\n<thead>\n<tr>\n<th rowspan=\"2\">Ministry/Agency</th>\n<th colspan=\"4\">Tota(...TRUNCATED) | "[{\"rows\": [{\"polygon\": [[0.0, 0.0], [3387.0, 0.0], [3387.0, 81.488], [0.0, 81.488]], \"confiden(...TRUNCATED) | "[{\"model\": \"datalab-to/surya-ocr-2\", \"model_name\": \"surya-ocr-2\", \"column_name\": \"markdo(...TRUNCATED) | |
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_031.png | "<table border=\"1\">\n<thead>\n<tr>\n<th rowspan=\"2\">Ministry/Agency</th>\n<th colspan=\"4\">Tota(...TRUNCATED) | "[{\"rows\": [{\"polygon\": [[3.391, 3.696], [3387.609, 3.696], [3387.609, 81.312], [3.391, 81.312]](...TRUNCATED) | "[{\"model\": \"datalab-to/surya-ocr-2\", \"model_name\": \"surya-ocr-2\", \"column_name\": \"markdo(...TRUNCATED) | |
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_032.png | "<table border=\"1\">\n<thead>\n<tr>\n<th rowspan=\"2\">Ministry/Agency</th>\n<th colspan=\"4\">Tota(...TRUNCATED) | "[{\"rows\": [{\"polygon\": [[3.39, 3.696], [3386.61, 3.696], [3386.61, 81.312], [3.39, 81.312]], \"(...TRUNCATED) | "[{\"model\": \"datalab-to/surya-ocr-2\", \"model_name\": \"surya-ocr-2\", \"column_name\": \"markdo(...TRUNCATED) | |
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_033.png | "<table border=\"1\">\n<thead>\n<tr>\n<th rowspan=\"2\">Ministry/Agency</th>\n<th colspan=\"4\">Tota(...TRUNCATED) | "[{\"rows\": [{\"polygon\": [[3.3890000000000002, 3.69], [3385.611, 3.69], [3385.611, 79.335], [3.38(...TRUNCATED) | "[{\"model\": \"datalab-to/surya-ocr-2\", \"model_name\": \"surya-ocr-2\", \"column_name\": \"markdo(...TRUNCATED) | |
PublicInvestmentProgram3YearRolling,FY2021-FY2023_page_034.png | "<table border=\"1\">\n<thead>\n<tr>\n<th rowspan=\"2\">Ministry/Agency</th>\n<th colspan=\"4\">Tota(...TRUNCATED) | "[{\"rows\": [{\"polygon\": [[3.39, 3.7], [3386.61, 3.7], [3386.61, 79.55], [3.39, 79.55]], \"confid(...TRUNCATED) | "[{\"model\": \"datalab-to/surya-ocr-2\", \"model_name\": \"surya-ocr-2\", \"column_name\": \"markdo(...TRUNCATED) |
End of preview. Expand in Data Studio
Surya OCR 2 (table) on sopheakvoatei/english-table-dataset-part3
Table recognition (mode full) over images in
sopheakvoatei/english-table-dataset-part3 using
Surya OCR 2 (650M, Qwen3.5-based) by Datalab, via the
surya-ocr package, run as offline vLLM batch
inference on Hugging Face Jobs.
Processing Details
- Source Dataset: sopheakvoatei/english-table-dataset-part3
- Model: datalab-to/surya-ocr-2
- Task:
table(table modefull) - Input column:
image(image) - Text column:
markdown(flattened, reading-order text per row) - Structured column:
surya_blocks(JSON: per-page blocks with bbox / polygon / label / reading_order / confidence / html) - Split:
train - Samples: 323
- Processed OK: 323 / 323
- Processing time: 19.5 min
- Date: 2026-08-07 06:57 UTC
License note
Surya's code is Apache-2.0, but the model weights use a modified OpenRAIL-M license: free for research, personal use, and startups under $5M funding/revenue, restricted from competitive use against Datalab's API. See the model card.
Dataset Structure
Original columns plus:
markdown: flattened text (OCR), label outline (layout), or table HTML (table)surya_blocks: structured result as a JSON string (one entry per page)inference_info: JSON list tracking models applied to this dataset
Generated with UV Scripts.
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