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import gradio as gr | |
import requests | |
import tensorflow as tf | |
import keras_ocr | |
import cv2 | |
import os | |
import numpy as np | |
import pandas as pd | |
from datetime import datetime | |
import scipy.ndimage.interpolation as inter | |
import easyocr | |
from PIL import Image | |
from paddleocr import PaddleOCR | |
import socket | |
# from send_email_user import send_user_email | |
from huggingface_hub import HfApi | |
import smtplib | |
# api = HfApi() | |
# api.upload_folder( | |
# folder_path="/media/pragnakalpl20/Projects/Pragnakalp_projects/gradio_demo/images", | |
# path_in_repo="my-dataset/images", | |
# repo_id="pragnakalp/OCR-image-to-text", | |
# repo_type="dataset", | |
# ignore_patterns="**/logs/*.txt", | |
# ) | |
# if not os.path.isdir('images'): | |
# os.mkdir('images') | |
# print("create folder--->") | |
print(os.getcwd()) | |
def get_device_ip_address(): | |
if os.name == "nt": | |
result = "Running on Windows" | |
hostname = socket.gethostname() | |
result += "\nHostname: " + hostname | |
host = socket.gethostbyname(hostname) | |
result += "\nHost-IP-Address:" + host | |
return result | |
elif os.name == "posix": | |
gw = os.popen("ip -4 route show default").read().split() | |
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) | |
s.connect((gw[2], 0)) | |
ipaddr = s.getsockname()[0] | |
gateway = gw[2] | |
host = socket.gethostname() | |
result = "\nIP address:\t\t" + ipaddr + "\r\nHost:\t\t" + host | |
return result | |
else: | |
result = os.name + " not supported yet." | |
return result | |
""" | |
Paddle OCR | |
""" | |
def ocr_with_paddle(img): | |
finaltext = '' | |
ocr = PaddleOCR(lang='en', use_angle_cls=True) | |
# img_path = 'exp.jpeg' | |
result = ocr.ocr(img) | |
for i in range(len(result[0])): | |
text = result[0][i][1][0] | |
finaltext += ' '+ text | |
return finaltext | |
""" | |
Keras OCR | |
""" | |
def ocr_with_keras(img): | |
output_text = '' | |
pipeline=keras_ocr.pipeline.Pipeline() | |
images=[keras_ocr.tools.read(img)] | |
predictions=pipeline.recognize(images) | |
first=predictions[0] | |
for text,box in first: | |
output_text += ' '+ text | |
return output_text | |
""" | |
easy OCR | |
""" | |
# gray scale image | |
def get_grayscale(image): | |
return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
# Thresholding or Binarization | |
def thresholding(src): | |
return cv2.threshold(src,127,255, cv2.THRESH_TOZERO)[1] | |
def ocr_with_easy(img): | |
gray_scale_image=get_grayscale(img) | |
thresholding(gray_scale_image) | |
cv2.imwrite('image.png',gray_scale_image) | |
reader = easyocr.Reader(['th','en']) | |
bounds = reader.readtext('image.png',paragraph="False",detail = 0) | |
bounds = ''.join(bounds) | |
return bounds | |
""" | |
Generate OCR | |
""" | |
def generate_ocr(Method,img): | |
try: | |
text_output = '' | |
print("Method___________________",Method) | |
if Method == 'EasyOCR': | |
text_output = ocr_with_easy(img) | |
if Method == 'KerasOCR': | |
text_output = ocr_with_keras(img) | |
if Method == 'PaddleOCR': | |
text_output = ocr_with_paddle(img) | |
# save_details(Method,text_output,img) | |
sender="pragnakalp.dev33@gmail.com" | |
password="httscgatatbbxxur" | |
reciever="pragnakalp.dev35@gmail.com" | |
s = smtplib('smtp.gmail.com', 587) | |
s.starttls() | |
s.ehlo() | |
# Pretend the SMTP server supports some forms of authentication. | |
s.esmtp_features['auth'] = 'LOGIN DIGEST-MD5 PLAIN' | |
s.login(sender,password) | |
message = """Subject : Appointment Booking\n\n | |
Hello, | |
Your OCR generated successfully""" | |
s.sendmail(sender, reciever, message) | |
s.quit() | |
mailsend=1 | |
print("Send mail successfully") | |
return text_output | |
# hostname = socket.gethostname() | |
# IPAddr = socket.gethostbyname(hostname) | |
# print(hostname) | |
# print("\nHost-IP-Address:" + IPAddr) | |
except Exception as e: | |
print("Error in ocr generation ==>",e) | |
text_output = "Something went wrong" | |
return text_output | |
""" | |
Save generated details | |
""" | |
def save_details(Method,text_output,img): | |
# print("//////////") | |
hostname = get_device_ip_address() | |
# url = 'https://pragnakalpdev33.pythonanywhere.com/HF_space_image_to_text' | |
# url = 'http://pragnakalpdev35.pythonanywhere.com/HF_space_image_to_text' | |
# myobj = {'Method': Method,'text_output':text_output,'img':img.tolist(),'hostname':hostname} | |
# x = requests.post(url, json = myobj) | |
# method = [] | |
# img_path = [] | |
# text = [] | |
# input_img = '' | |
# hostname = '' | |
# picture_path = "image.jpg" | |
# curr_datetime = datetime.now().strftime('%Y-%m-%d %H-%M-%S') | |
# if text_output: | |
# splitted_path = os.path.splitext(picture_path) | |
# modified_picture_path = splitted_path[0] + curr_datetime + splitted_path[1] | |
# cv2.imwrite("myimage.jpg", img) | |
# with open('savedata.txt', 'w') as f: | |
# print("write test") | |
# f.write("testdata") | |
# print("write Successfully") | |
# # img = Image.open(r"/home/user/app/") | |
# # img.save(modified_picture_path) | |
# input_img = modified_picture_path | |
# try: | |
# df = pd.read_csv("AllDetails.csv") | |
# df2 = {'method': Method, 'input_img': input_img, 'generated_text': text_output} | |
# df = df.append(df2, ignore_index = True) | |
# df.to_csv("AllDetails.csv", index=False) | |
# except: | |
# method.append(Method) | |
# img_path.append(input_img) | |
# text.append(text_output) | |
# dict = {'method': method, 'input_img': img_path, 'generated_text': text} | |
# df = pd.DataFrame(dict,index=None) | |
# df.to_csv("AllDetails.csv") | |
return send_user_email() | |
# return x | |
""" | |
Create user interface for OCR demo | |
""" | |
image = gr.Image(shape=(224, 224),elem_id="img_div") | |
method = gr.Radio(["EasyOCR", "KerasOCR", "PaddleOCR"],elem_id="radio_div") | |
output = gr.Textbox(label="Output") | |
demo = gr.Interface( | |
generate_ocr, | |
[method,image], | |
output, | |
title="Optical Character Recognition", | |
description="Try OCR with different methods", | |
theme="darkpeach", | |
css=".gradio-container {background-color: lightgray} #radio_div {background-color: #FFD8B4; font-size: 40px;}", | |
allow_flagging = "manual" | |
) | |
demo.launch(enable_queue = False) |