Datasets:
TextRenderLab OCR Dataset
This dataset is a synthetic OCR instruction-tuning dataset built with TextRenderLab. It contains rendered text images paired with OCR prompts and full transcription targets in both Traditional Chinese and English.
Dataset Summary
- Task: image-to-text OCR transcription
- Languages: Traditional Chinese, English
- Total samples: 40,000
- Language split:
- Chinese: 20,000
- English: 20,000
- Image format: PNG
- Annotation format: JSONL
Each sample contains:
- A rendered image path under
images/ - An OCR-style user question in Chinese
- A full text transcription as the answer
- Chat-style fields for multimodal training pipelines
Data Structure
Each line in dataset.jsonl is a JSON object with the following fields:
| Field | Type | Description |
|---|---|---|
unique_id |
string |
Unique sample identifier |
images |
list[string] |
Relative image path list, typically one PNG file |
question |
string |
OCR prompt |
answer |
string |
Full transcription target |
messages |
list[object] |
Chat-style training format with <image> prompt |
axolotl_messages |
list[object] |
Axolotl-compatible multimodal message format |
Example
{
"unique_id": "0ff0e0d5-afcf-48aa-a08b-c6d1a1ddc5eb",
"images": ["images/en_ocr_00000.png"],
"question": "圖片裡有些字,請幫我轉錄出來。",
"answer": "Under the legal framework that defined Hong Kong’s semi-autonomy after its return to China in 1997, many in the territory assumed that it would mostly manage its own affairs for decades.",
"messages": [
{"role": "user", "content": "<image>圖片裡有些字,請幫我轉錄出來。"},
{"role": "assistant", "content": "Under the legal framework that defined Hong Kong’s semi-autonomy after its return to China in 1997, many in the territory assumed that it would mostly manage its own affairs for decades."}
],
"axolotl_messages": [
{
"role": "user",
"content": [
{"type": "image", "url": "images/en_ocr_00000.png"},
{"type": "text", "text": "圖片裡有些字,請幫我轉錄出來。"}
]
},
{
"role": "assistant",
"content": [
{"type": "text", "text": "Under the legal framework that defined Hong Kong’s semi-autonomy after its return to China in 1997, many in the territory assumed that it would mostly manage its own affairs for decades."}
]
}
]
}
Intended Use
This dataset is intended for:
- OCR fine-tuning for multimodal LLMs
- Image-text transcription training
- Bilingual OCR robustness experiments
- Synthetic pretraining or instruction-tuning pipelines
Notes
- The images are synthetically rendered rather than photographed.
- Prompts are phrased in Chinese, while answers may be either Chinese or English depending on the source text.
- Relative image paths in
imagesassume the repository or dataset root contains bothdataset.jsonland theimages/directory.
Loading Example
import json
from pathlib import Path
dataset_path = Path("dataset.jsonl")
with dataset_path.open("r", encoding="utf-8") as f:
first = json.loads(next(f))
print(first["images"])
print(first["question"])
print(first["answer"][:200])
Citation
If you use this dataset, please cite or reference the Hugging Face dataset repository:
minyichen/Render-OCR
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