32 lines
1.3 KiB
Python
32 lines
1.3 KiB
Python
import gradio as gr
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from transformers import TrOCRProcessor, VisionEncoderDecoderModel
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def inference(img):
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pretrained_model_path = "trocr-small-handwritten"
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image = img.convert("RGB")
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processor = TrOCRProcessor.from_pretrained(pretrained_model_path)
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model = VisionEncoderDecoderModel.from_pretrained(pretrained_model_path)
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pixel_values = processor(images=image, return_tensors="pt").pixel_values
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generated_ids = 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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title = "OCR:trocr-small-handwritten"
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description = "这是trocr-small-handwritten的Gradio Demo。上传你想要的图像或者点击下面的示例来加载它。"
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article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>"
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examples=[['ocr_example.jpg']]
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demo = gr.Interface(
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fn=inference,
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inputs=[gr.inputs.Image(type="pil")],
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outputs=gr.outputs.Textbox(),
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title=title,
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description=description,
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article=article,
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examples=examples)
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demo.launch(server_name="0.0.0.0") |