
### How to use

Here is how to use this model in PyTorch:

```python
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
from PIL import Image

processor = TrOCRProcessor.from_pretrained('dsupa/mangaocr-hoogberta-v2')
model = VisionEncoderDecoderModel.from_pretrained('dsupa/mangaocr-hoogberta-v2')

def predict(image_path):
    image = Image.open(image_path).convert("RGB")
    pixel_values = processor(images=image, return_tensors="pt").pixel_values
    generated_ids = model.generate(pixel_values)
    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]

    return generated_text

image_path = "your_img.jpg"
pred = predit(image_path)
print(pred)
```
{"tags": ["trocr", "image-to-text"], "widget": [{"src": "https://huggingface.co/dsupa/mangaocr-hoogberta-v1/to_test_hf_model/test1.JPG", "example_title": "test 1"}, {"src": "https://huggingface.co/dsupa/mangaocr-hoogberta-v1/to_test_hf_model/test2.JPG", "example_title": "test 2"}, {"src": "https://huggingface.co/dsupa/mangaocr-hoogberta-v1/to_test_hf_model/test3.JPG", "example_title": "test 3"}, {"src": "https://huggingface.co/dsupa/mangaocr-hoogberta-v1/to_test_hf_model/test4.JPG", "example_title": "test 4"}, {"src": "https://huggingface.co/dsupa/mangaocr-hoogberta-v1/to_test_hf_model/test5.JPG", "example_title": "test 5"}, {"src": "https://huggingface.co/dsupa/mangaocr-hoogberta-v1/to_test_hf_model/test6.JPG", "example_title": "test 6"}]}
transformers pytorch tensorboard vision-encoder-decoder trocr image-to-text endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #vision-encoder-decoder #trocr #image-to-text #endpoints_compatible #region-us 


### How to use

Here is how to use this model in PyTorch:


### How to use

Here is how to use this model in PyTorch:
TAGS
#transformers #pytorch #tensorboard #vision-encoder-decoder #trocr #image-to-text #endpoints_compatible #region-us 
 ### How to use

Here is how to use this model in PyTorch:
TAGS
#transformers #pytorch #tensorboard #vision-encoder-decoder #trocr #image-to-text #endpoints_compatible #region-us 
### How to use

Here is how to use this model in PyTorch: