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| import pandas as pd | |
| import PIL | |
| from PIL import Image | |
| from PIL import ImageDraw | |
| from PIL import ImageFont | |
| import gradio as gr | |
| import torch | |
| import easyocr | |
| import cv2 as cv | |
| import math | |
| from numpy import asarray | |
| import numpy as np | |
| torch.hub.download_url_to_file('https://i.pinimg.com/736x/93/d3/54/93d354497ea26d5dc181055b9356cf79.jpg', 'korean.jpg') | |
| torch.hub.download_url_to_file('https://64.media.tumblr.com/1a5796817934a179664508693cae82d3/67c2ea7948c385cc-1b/s1280x1920/a70d4fcc0a5528de415b024db4ee6036da9c4c35.jpg', 'chinese.jpg') | |
| torch.hub.download_url_to_file('https://digistatement.com/wp-content/uploads/2020/06/12a7c208-33bb-4a91-bfc2-1510a18499e9.jpg', 'japanese.jpg') | |
| torch.hub.download_url_to_file('https://img.mghubcdn.com/file/imghub/moriarty-the-patriot/68/10.jpg', 'english.jpg') | |
| def midpoint(x1, y1, x2, y2): | |
| x_mid = int((x1 + x2)/2) | |
| y_mid = int((y1 + y2)/2) | |
| return (x_mid, y_mid) | |
| def draw_mask(img, bounds): | |
| mask = np.zeros(img.shape[:2], dtype="uint8") | |
| for bound in bounds: | |
| box0, box1, box2, box3 = bound[0] | |
| x0, y0 = box0 | |
| x1, y1 = box1 | |
| x2, y2 = box2 | |
| x3, y3 = box3 | |
| x_mid0, y_mid0 = midpoint(x1, y1, x2, y2) | |
| x_mid1, y_mi1 = midpoint(x0, y0, x3, y3) | |
| thickness = int(math.sqrt((x2 - x1)**2 + (y2 - y1)**2)) | |
| cv.line(mask, (x_mid0, y_mid0), (x_mid1, y_mi1), 255, thickness) | |
| img = cv.inpaint(img, mask, 3, cv.INPAINT_TELEA) | |
| return(img) | |
| def inference(img, lang): | |
| if lang == "english": | |
| lang = ['en'] | |
| elif lang == "chinese": | |
| lang = ['ch_sim'] | |
| elif lang == "korean": | |
| lang = ['ko'] | |
| else: | |
| lang = ['ja'] | |
| reader = easyocr.Reader(lang) | |
| bounds = reader.readtext(img.name) | |
| im = PIL.Image.open(img.name) | |
| img_array = np.array(im) | |
| img = draw_mask(img_array, bounds) | |
| img = Image.fromarray(im, 'RGB') | |
| lang = "" | |
| im.save('box.jpb') | |
| img.save('result.jpg') | |
| return ['box.jpg', 'result.jpg', pd.DataFrame(bounds). iloc[: , 1:2]] | |
| title = 'Manga Image Cleaner' | |
| description = 'Image inpainting and text detection demo with the use of EasyOCR and CV2. To use it, simply upload your image and choose a language from the dropdown menu, or click one of the examples to test the program.' | |
| article = "<p style='text-align: center'><a href='https://www.jaided.ai/easyocr/'>Ready-to-use image inpainting with supported languages such as: Chinese, English, Japanese, and Korean</a> | <a href='https://github.com/JaidedAI/EasyOCR'>Github OCR Repo</a> | <a href='https://towardsdatascience.com/remove-text-from-images-using-cv2-and-keras-ocr-24e7612ae4f4'>CV2 Reference</a></p>" | |
| css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}" | |
| examples = [['chinese.jpg',"chinese"], ['english.jpg',"english"], ['japanese.jpg',"japanese"], ['korean.jpg',"korean"]] | |
| choices = [ | |
| "chinese", | |
| "english", | |
| "japanese", | |
| "korean" | |
| ] | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Image(type='file', label='Input'),gr.inputs.Dropdown(choices, type="value", default="korean", label='language')], | |
| [gr.outputs.Image(type='file', label='Output'), | |
| gr.outputs.Image(type='file', label='Output'), | |
| gr.outputs.Dataframe()], | |
| title=title, | |
| description=description, | |
| article=article, | |
| examples=examples, | |
| css=css, | |
| enable_queue=True | |
| ).launch(debug=True) |