trocr-base-printed / pipeline.py
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from typing import Dict, List, Any
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
class PreTrainedPipeline():
def __init__(self, path=""):
self.processor = TrOCRProcessor.from_pretrained(path)
self.model = VisionEncoderDecoderModel.from_pretrained(path)
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
image = data.pop("inputs", data)
# process image
pixel_values = self.processor(images=image, return_tensors="pt").pixel_values
# run prediction
generated_ids = self.model.generate(pixel_values)
# decode output
prediction = generated_text = self.processor.batch_decode(generated_ids, skip_special_tokens=True)
return {"text":prediction[0]}