39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
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import gradio as gr
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from gradio.themes.utils import sizes
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theme = gr.themes.Default(radius_size=sizes.radius_none).set(
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block_label_text_color = '#4D63FF',
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block_title_text_color = '#4D63FF',
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button_primary_text_color = '#4D63FF',
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button_primary_background_fill='#FFFFFF',
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button_primary_border_color='#4D63FF',
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button_primary_background_fill_hover='#EDEFFF',
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)
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processor = TrOCRProcessor.from_pretrained('microsoft/trocr-base-printed')
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model = VisionEncoderDecoderModel.from_pretrained('microsoft/trocr-base-printed')
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def ocr(image):
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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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return generated_text
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demo = gr.Interface(fn=ocr,
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inputs='image',
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outputs='text',
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theme = theme,
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css = "footer {visibility: hidden}",
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allow_flagging = "never",
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examples = ['printed.jpg'])
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if __name__ == "__main__":
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# demo.queue(concurrency_count=3)
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demo.launch(server_name = "0.0.0.0")
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#demo.launch()
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