Upload files to 'Electrol'
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from flask import Flask, render_template, request, redirect, Response, send_file
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import glob
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from pdf2image import convert_from_path
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from PyPDF2 import PdfReader
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import pandas as pd
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import csv
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import os
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import cv2
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import numpy as np
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from paddleocr import PaddleOCR, draw_ocr
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import re
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#ocr = PaddleOCR(use_angle_cls=True, lang='en', use_space_char=True, show_log=False,type='structure',image_enhance=True)
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app = Flask(__name__)
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@app.route('/pdftotext', methods=["POST"])
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def pdftotext():
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Dataset = request.get_json()
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data = {'visiting': Dataset}
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for i in data['visiting']:
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import time
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#time.sleep(1)
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a = i
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x = a['FileData']
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# print(x)
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y = a['FileName']
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z = a['FileType']
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# CreatedBy=a['CreatedBy']
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name = y + '.' + z
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print(name)
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# print(y)
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# image = y.split("/")
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# filename=image[-1]
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# print(x)
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img_data = x.encode()
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import base64
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with open('./uploads/' + name, "wb") as fh:
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fh.write(base64.decodebytes(img_data))
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# pdf to images
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images = convert_from_path('./uploads/' + name)
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for i in range(len(images)):
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images[i].save('./images/'+ str(i) +'.jpg', 'JPEG')
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#count of a pdf files
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reader = PdfReader('./uploads/' + name)
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num = len(reader.pages)
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print(num)
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import pandas as pd
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ocr = PaddleOCR(use_gpu=True,use_angle_cls=True, lang='en', use_space_char=True, show_log=False,type='structure',image_enhance=True)
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dframe = pd.DataFrame({'Name': [], 'Father Name': [], 'Mother Name':[],'Husband Name':[],'Wife Name':[] , 'Others Name':[] ,'House Number': [],'Age': [], 'Gender': [],'Voter Number':[]})
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# Assuming 'dframe' is the DataFrame with column names
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with open(y+'.csv', 'a', newline='') as csvfile:
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writer = csv.DictWriter(csvfile, fieldnames=dframe.columns)
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writer.writeheader()
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list_of_elements=[]
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for i in range(num):
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path='./images/'+ str(i)+'.jpg'
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print(path)
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img = cv2.imread(path)
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if img.shape[0] > 1000:
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img = cv2.resize(img, (int(img.shape[1]*0.7), int(img.shape[0]*0.7)))
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result1 = ocr.ocr(img)
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txts1 = [line[1][0] for line in result1[0]]
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#print(txts1)
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for i in txts1:
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if 'Section' in i:
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street = (i.split(':')[-1])
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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ret, thresh = cv2.threshold(gray, 250, 300, cv2.THRESH_BINARY)
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contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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import pandas as pd
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min_size = 9000
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max_size = 100000
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# Sort contours based on y-coordinate and then x-coordinate
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contours = sorted(contours, key=lambda contour: (cv2.boundingRect(contour)[1], cv2.boundingRect(contour)[0]))
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# Extract text from each contour
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for contour in contours:
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x, y, w, h = cv2.boundingRect(contour)
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box_size = w * h
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if box_size >= min_size and box_size <= max_size:
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# Draw bounding box around contour
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cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
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# for contour in contours:
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# x, y, w, h = cv2.boundingRect(contour)
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# box_size = w * h
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# if box_size >= min_size and box_size <= max_size:
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# cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 1)
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# cv2.putText(img, "Box", (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
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box = img[y:y + h, x:x + w]
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#cv2_imshow(box)
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result = ocr.ocr(box)
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try:
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txts = [line[1][0] for line in result[0]]
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txts.remove('Photo is')
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txts.remove('Available')
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age = [re.findall(r"\d{2}", i)[0] for i in txts if "Age" in i and re.findall(r"\d{2}", i)]
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voter_ID = [element for element in txts if
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element.isalnum() and not element.isalpha() and not element.isdigit()]
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all_data = [item.lower().replace('name', 'Name:').replace('number', 'Number:').replace("gender", "',Gender:'")
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for item in txts]
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all_data[0] = ":" + all_data[0]
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all_data[1] = ":" + all_data[1]
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for i in range(1, len(all_data)):
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if ":" not in all_data[i]:
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all_data[i - 1] += " " + all_data[i]
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all_data[i] = ""
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# Remove empty elements from the list
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my_list = [element for element in all_data if element != ""]
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# my_list = [all_data[i-1] + " " + all_data[i] if ":" not in all_data[i] else all_data[i] for i in range(0, len(all_data)) if all_data[i] != ""]
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my_list = [my_list[i][1:] if my_list[i].startswith(":") else my_list[i] for i in range(len(my_list))]
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my_list = [s.replace('::', ':') for s in my_list]
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list_of_elements.append("Age: " + age[0])
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list_of_elements.append("Voter Number: " + voter_ID[0])
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for i in my_list:
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if i.startswith("Name"):
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person_name = i.split(":")[-1].upper()
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list_of_elements.append("Name: " + person_name)
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elif "father" in i:
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fathername = i.split(":")[-1].upper()
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list_of_elements.append("Father Name: " + fathername)
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elif "husband" in i:
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husband_name = i.split(":")[-1].upper()
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list_of_elements.append("Husband Name: " + husband_name)
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elif "mother" in i:
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mother_name = i.split(":")[-1].upper()
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list_of_elements.append("Mother Name: " + mother_name)
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elif "Gender" in i:
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gender = i.split(":")[-1].upper()
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list_of_elements.append("Gender: " + gender)
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elif "house" in i:
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house = i.split(":")[-1].upper()
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list_of_elements.append("House Number: " + house + ',' + street)
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elif "wife" in i:
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wife = i.split(":")[-1].upper()
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list_of_elements.append("Wife Name: " + wife)
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elif "other" in i:
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other = i.split(":")[-1].upper()
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list_of_elements.append("Others Name: " + other)
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df = pd.DataFrame(list_of_elements)
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#df=df.T
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data = dict([val.split(': ') for val in df[0]])
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list_of_elements.clear()
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print(data)
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writer.writerow(data)
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csvfile.flush()
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except (IndexError,ValueError):
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pass
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files = glob.glob('D:\\text_extraction\\uploads\\*')
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for f in files:
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os.remove(f)
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files = glob.glob('D:\\text_extraction\\images\\*')
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for f in files:
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os.remove(f)
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return 'done'
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if __name__ == "__main__":
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app.run(host='0.0.0.0',port=1112)
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