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Upload app.py
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app.py
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import pandas as pd
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import PIL
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from PIL import Image
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from PIL import ImageDraw
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import gradio as gr
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import torch
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import easyocr
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torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/english.png', 'english.png')
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torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/chinese.jpg', 'chinese.jpg')
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torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/japanese.jpg', 'japanese.jpg')
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torch.hub.download_url_to_file('https://i.imgur.com/mwQFd7G.jpeg', 'Hindi.jpeg')
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def draw_boxes(image, bounds, color='yellow', width=2):
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draw = ImageDraw.Draw(image)
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for bound in bounds:
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p0, p1, p2, p3 = bound[0]
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draw.line([*p0, *p1, *p2, *p3, *p0], fill=color, width=width)
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return image
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def inference(img, lang):
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reader = easyocr.Reader(lang)
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bounds = reader.readtext(img.name)
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im = PIL.Image.open(img.name)
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draw_boxes(im, bounds)
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im.save('result.jpg')
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return ['result.jpg', pd.DataFrame(bounds).iloc[: , 1:]]
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title = 'Image To Optical Character Recognition'
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description = 'Multilingual OCR which works conveniently on all devices in multiple languages.'
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article = "<p style='text-align: center'></p>"
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examples = [['english.png',['en']],['chinese.jpg',['ch_sim', 'en']],['japanese.jpg',['ja', 'en']],['Hindi.jpeg',['hi', 'en']]]
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css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
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choices = [
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"ch_sim",
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"ch_tra",
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"de",
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"en",
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"es",
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"ja",
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"hi",
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"ru"
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]
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gr.Interface(
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inference,
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[gr.inputs.Image(type='file', label='Input'),gr.inputs.CheckboxGroup(choices, type="value", default=['en'], label='language')],
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[gr.outputs.Image(type='file', label='Output'), gr.outputs.Dataframe(headers=['text', 'confidence'])],
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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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css=css,
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enable_queue=True
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).launch(debug=True)
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