40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
from transformers import pipeline
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import gradio as gr
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import cv2
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from PIL import Image
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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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image_to_text = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
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def ocr(image):
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inp = Image.fromarray(image.astype('uint8'), 'RGB')
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text = image_to_text(inp)
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total_caption = ""
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for caption in text:
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total_caption = total_caption + caption.get('generated_text')
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total_caption = total_caption + '\r\n'
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return total_caption
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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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examples = ['soccer.jpg'])
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if __name__ == "__main__":
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demo.queue(concurrency_count=10).launch(server_name = "0.0.0.0")
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