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import gradio as gr
import pandas as pd
import numpy as np
import easyocr
import torch
import cv2
import PIL
from PIL import ImageFont, ImageDraw, Image
lang_id = {
"Afrikaans": "af",
"Amharic": "am",
"Arabic": "ar",
"Asturian": "ast",
"Azerbaijani": "az",
"Bashkir": "ba",
"Belarusian": "be",
"Bulgarian": "bg",
"Bengali": "bn",
"Breton": "br",
"Bosnian": "bs",
"Catalan": "ca",
"Cebuano": "ceb",
"Czech": "cs",
"Welsh": "cy",
"Danish": "da",
"German": "de",
"Greeek": "el",
"English": "en",
"Spanish": "es",
"Estonian": "et",
"Persian": "fa",
"Fulah": "ff",
"Finnish": "fi",
"French": "fr",
"Western Frisian": "fy",
"Irish": "ga",
"Gaelic": "gd",
"Galician": "gl",
"Gujarati": "gu",
"Hausa": "ha",
"Hebrew": "he",
"Hindi": "hi",
"Croatian": "hr",
"Haitian": "ht",
"Hungarian": "hu",
"Armenian": "hy",
"Indonesian": "id",
"Igbo": "ig",
"Iloko": "ilo",
"Icelandic": "is",
"Italian": "it",
"Japanese": "ja",
"Javanese": "jv",
"Georgian": "ka",
"Kazakh": "kk",
"Central Khmer": "km",
"Kannada": "kn",
"Korean": "ko",
"Luxembourgish": "lb",
"Ganda": "lg",
"Lingala": "ln",
"Lao": "lo",
"Lithuanian": "lt",
"Latvian": "lv",
"Malagasy": "mg",
"Macedonian": "mk",
"Malayalam": "ml",
"Mongolian": "mn",
"Marathi": "mr",
"Malay": "ms",
"Burmese": "my",
"Nepali": "ne",
"Dutch": "nl",
"Norwegian": "no",
"Northern Sotho": "ns",
"Occitan": "oc",
"Oriya": "or",
"Panjabi": "pa",
"Polish": "pl",
"Pushto": "ps",
"Portuguese": "pt",
"Romanian": "ro",
"Russian": "ru",
"Sindhi": "sd",
"Sinhala": "si",
"Slovak": "sk",
"Slovenian": "sl",
"Somali": "so",
"Albanian": "sq",
"Serbian": "sr",
"Swati": "ss",
"Sundanese": "su",
"Swedish": "sv",
"Swahili": "sw",
"Tamil": "ta",
"Thai": "th",
"Tagalog": "tl",
"Tswana": "tn",
"Turkish": "tr",
"Ukrainian": "uk",
"Urdu": "ur",
"Uzbek": "uz",
"Vietnamese": "vi",
"Wolof": "wo",
"Xhosa": "xh",
"Yiddish": "yi",
"Yoruba": "yo",
"Chinese": "zh",
"Zulu": "zu",
}
ocr_lang=[
'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',
]
def blur_im(img,bounds):
im = cv2.imread(img)
im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
for bound in bounds:
p0, p1, p2, p3 = bound[0]
x = int(p0[0])
y = int(p0[1])
w = int(p2[0]) - int(x)
h = int(p2[1]) - int(y)
kernel = np.ones((5, 5), np.uint8)
im[y:y+h, x:x+w] = cv2.dilate(im[y:y+h, x:x+w], kernel, iterations=2)
im[y:y+h, x:x+w] = cv2.GaussianBlur(im[y:y+h, x:x+w],(51,51),0)
#fontpath = "tamil/Latha.ttf"
text = "New Text"
#fnt = ImageFont.truetype("Pillow/Tests/fonts/FreeMono.ttf", 40)
font = ImageFont.load("arial.pil", 40)
#font = ImageFont.truetype(fontpath, 32)
im = Image.fromarray(im)
for bound in bounds:
p0, p1, p2, p3 = bound[0]
x = int(p0[0])
y = int(p0[1])
w = int(p2[0]) - int(x)
h = int(p2[1]) - int(y)
draw = ImageDraw.Draw(im)
draw.text((x+5, y+5),text, font = font, fill=(0,0,0))
#img_tamil = np.array(img_pil)
return im
def draw_boxes(image, bounds, color='blue', width=1):
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 detect(img, target_lang,target_lang2=None):
if target_lang2 != None and target_lang2 != "":
lang=f"{lang_id[target_lang]}"
lang2=f"{lang_id[target_lang2]}"
lang=[lang,lang2]
else:
lang=[f"{lang_id[target_lang]}"]
pass
#global bounds
reader = easyocr.Reader(lang)
bounds = reader.readtext(img)
im = PIL.Image.open(img)
im_out=draw_boxes(im, bounds)
#im.save('result.jpg')
blr_out=blur_im(img,bounds)
return im_out,blr_out,pd.DataFrame(bounds),pd.DataFrame(bounds).iloc[:,1:]
with gr.Blocks() as robot:
with gr.Row():
with gr.Column():
im=gr.Image(type="filepath")
with gr.Column():
with gr.Row():
target_lang = gr.Dropdown(label="Detect language", choices=list(lang_id.keys()),value="English")
target_lang2 = gr.Dropdown(label="Detect language", choices=list(lang_id.keys()),value="")
go_btn=gr.Button()
with gr.Row():
with gr.Column():
out_im=gr.Image()
with gr.Column():
out_txt=gr.Textbox(lines=8)
data_f=gr.Dataframe()
with gr.Row():
with gr.Column():
trans_im=gr.Image()
gr.Column()
go_btn.click(detect,[im,target_lang,target_lang2],[out_im,trans_im,out_txt,data_f])
robot.queue(concurrency_count=10).launch() |