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---
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license: openrail
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---
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# trocr-old-russian
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## Info
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The model is trained to recognize printed texts in Old Russian language
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- Use microsoft/trocr-small-printed as base model for fine-tune.
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- Fine-tune on 636k text images from dataset: https://huggingface.co/datasets/nevmenandr/russian-old-orthography-ocr
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## Usage
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### Base-usage
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```python
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from PIL import Image
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from transformers import TrOCRProcessor, VisionEncoderDecoderModel
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hf_model = VisionEncoderDecoderModel.from_pretrained("Serovvans/trocr-prereform-orthography")
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image = Image.open("./path/to/your/image")
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processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-printed")
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pixel_values = processor(images=image, return_tensors="pt").pixel_values
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generated_ids = hf_model.generate(pixel_values)
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generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
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print(generated_text)
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```
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## Usage for recognizing the book
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```python
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```
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## Metrics on test
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- CER (Char Error Rate) = 0.095
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- WER (Word Error Rate) = 0.298 |
