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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/thai.jpg', 'thai.jpg')
torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/french.jpg', 'french.jpg')
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://github.com/JaidedAI/EasyOCR/raw/master/examples/korean.png', 'korean.png')
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 = 'EasyOCR'
description = 'Gradio demo for EasyOCR. EasyOCR demo supports 80+ languages.To use it, simply upload your image and choose a language from the dropdown menu, or click one of the examples to load them. Read more at the links below.'
article = "<p style='text-align: center'><a href='https://www.jaided.ai/easyocr/'>Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.</a> | <a href='https://github.com/JaidedAI/EasyOCR'>Github Repo</a></p>"
examples = [['english.png',['en']],['thai.jpg',['th']],['french.jpg',['fr', 'en']],['chinese.jpg',['ch_sim', 'en']],['japanese.jpg',['ja', 'en']],['korean.png',['ko', 'en']],['Hindi.jpeg',['hi', 'en']]]
css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
choices = [
"abq",
"ady",
"af",
"ang",
"ar",
"as",
"ava",
"az",
"be",
"bg",
"bh",
"bho",
"bn",
"bs",
"ch_sim",
"ch_tra",
"che",
"cs",
"cy",
"da",
"dar",
"de",
"en",
"es",
"et",
"fa",
"fr",
"ga",
"gom",
"hi",
"hr",
"hu",
"id",
"inh",
"is",
"it",
"ja",
"kbd",
"kn",
"ko",
"ku",
"la",
"lbe",
"lez",
"lt",
"lv",
"mah",
"mai",
"mi",
"mn",
"mr",
"ms",
"mt",
"ne",
"new",
"nl",
"no",
"oc",
"pi",
"pl",
"pt",
"ro",
"ru",
"rs_cyrillic",
"rs_latin",
"sck",
"sk",
"sl",
"sq",
"sv",
"sw",
"ta",
"tab",
"te",
"th",
"tjk",
"tl",
"tr",
"ug",
"uk",
"ur",
"uz",
"vi"
]
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) |