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| from transformers import VisionEncoderDecoderModel | |
| from transformers import TrOCRProcessor, AutoTokenizer, ViTImageProcessor | |
| import gradio as gr | |
| from PIL import Image | |
| def OCR(image): | |
| model = VisionEncoderDecoderModel.from_pretrained("kavg/TrOCR-SIN-DeiT-Handwritten") | |
| tokenizer = AutoTokenizer.from_pretrained('NLPC-UOM/SinBERT-large') | |
| feature_extractor = ViTImageProcessor.from_pretrained("google/vit-base-patch16-224") | |
| processor = TrOCRProcessor(image_processor=feature_extractor, tokenizer=tokenizer) | |
| pixel_values = processor(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 | |
| demo = gr.Interface(fn=OCR, inputs=gr.Image(show_label=False, type="pil"),outputs=gr.Textbox()) | |
| demo.launch(share=True, debug=True) |