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| from pdf2image import convert_from_path | |
| import base64 | |
| from io import BytesIO | |
| import pandas as pd | |
| import PIL | |
| import numpy as np | |
| 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/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): | |
| global img1,bounds | |
| img1= img | |
| reader = easyocr.Reader(lang) | |
| bounds = reader.readtext(img) | |
| try: | |
| #bounds = reader.readtext(img) | |
| im = PIL.Image.open(img) | |
| except: | |
| im = PIL.Image.fromarray(img) | |
| draw_boxes(im, bounds) | |
| cdf = pd.DataFrame([x[1:] for x in bounds],columns=['text','confidence']) | |
| cdf['confidence'] = cdf['confidence'].apply(lambda x:"{0:.1%}".format(x)) | |
| return [im, cdf] | |
| def read_from_file(file_path,lang): | |
| if '.pdf' in str(file_path): | |
| print('pdf') | |
| # Convert each page of the PDF into an image | |
| pages = convert_from_path(file_path) | |
| # Convert each page image to base64 and append to the list | |
| data = [] | |
| imgs = [] | |
| n = 0 | |
| for i, page in enumerate(pages): | |
| if n>=5: | |
| break | |
| # Save the page image to a byte buffer | |
| img,dfx = inference(np.array(page)[:, :, ::-1],lang) | |
| imgs.append(img) | |
| dfx['page'] = n | |
| data.append(dfx) | |
| n+=1 | |
| data = pd.concat(data).reset_index(drop=True) | |
| data | |
| return [imgs,data] | |
| else: | |
| print('image') | |
| img2 = np.array(PIL.Image.open(file_path)) | |
| a,b = inference(img2,lang) | |
| return [[a],b] | |
| title = 'Gradio OCR Demo' | |
| description = 'Gradio OCR 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.' | |
| examples = [['english.png',['en']],['japanese.jpg',['ja', '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'] | |
| app = gr.Interface( | |
| read_from_file, | |
| inputs=[gr.File(type='filepath',label='input_file pdf or image'),#gr.Image(type='filepath', label='Input'), | |
| gr.CheckboxGroup(choices, type="value", label='language')], | |
| outputs=[gr.Gallery(columns=4), 'dataframe'], | |
| title=title, | |
| description=description, | |
| examples=examples, | |
| css=css | |
| ) | |
| app.launch(debug=True,enable_queue=True) |