| 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) |