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---

license: openrail
---

# trocr-old-russian
## Info
The model is trained to recognize printed texts in Old Russian language
- Use microsoft/trocr-small-printed as base model for fine-tune.
- Fine-tune on 636k text images from dataset: https://huggingface.co/datasets/nevmenandr/russian-old-orthography-ocr

## Usage
### Base-usage
```python

from PIL import Image

from transformers import TrOCRProcessor, VisionEncoderDecoderModel



hf_model = VisionEncoderDecoderModel.from_pretrained("Serovvans/trocr-prereform-orthography")



image = Image.open("./path/to/your/image")



processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-printed")

pixel_values = processor(images=image, return_tensors="pt").pixel_values



generated_ids = hf_model.generate(pixel_values)

generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]

print(generated_text)

```
## Usage for recognizing the book
```python

```

## Metrics on test
- CER (Char Error Rate) = 0.095
- WER (Word Error Rate) = 0.298