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