punjab_mpi.py

#!/usr/bin/env python
# coding: utf-8

import traceback
sys.path.append('../')

import os
import pdf2image
from PIL import Image
import pytesseract
import difflib
import re
import pandas as pd
import sys
from helper import *
import argparse
import multiprocessing
import time
from datetime import datetime
import shutil
from tempfile import mkstemp
from mpi4py.futures import MPIPoolExecutor

if False:

    script_description = """ punjab parsing """

    parser = argparse.ArgumentParser(description=script_description,
                                     formatter_class=argparse.ArgumentDefaultsHelpFormatter)

    parser.add_argument("data_path", help="data path of the states with append /")
    parser.add_argument("state_name", help="the exact state name of data with /")

    cli_args = parser.parse_args()

    DATA_PATH = cli_args.data_path
    STATE = cli_args.state_name


DATA_PATH = '/share/svasudevan2lab/parse_in_rolls/data/'
STATE = 'punjab/'

PARSE_DATA_PAGES = "/share/svasudevan2lab/parse_in_rolls/parseData/images/"+STATE
create_path(PARSE_DATA_PAGES)

PARSE_DATA_BLOCKS = "/share/svasudevan2lab/parse_in_rolls/parseData/blocks/"+STATE
create_path(PARSE_DATA_BLOCKS)

PARSE_DATA_CSVS = "/share/svasudevan2lab/parse_in_rolls/parseData/csvs/"+STATE
create_path(PARSE_DATA_CSVS)

COLUMNS = ["number","id", "elector_name", "father_or_husband_name", "relationship", "house_no", "age", "sex", "ac_name", "parl_constituency", "part_no", "year", "state", "filename", "main_town", "police_station", "mandal", "revenue_division", "district", "pin_code", "polling_station_name", "polling_station_address", "net_electors_male", "net_electors_female", "net_electors_third_gender", "net_electors_total"]

state_pdfs_path = DATA_PATH+STATE
state_pdfs_files = os.listdir(state_pdfs_path)
sort_nicely(state_pdfs_files)


def extract_4_numbers(crop_stat_path):
    
    text = (pytesseract.image_to_string(crop_stat_path, config='--psm 11', lang='eng')) #config='--psm 4' config='-c preserve_interword_spaces=1'
    text = re.findall(r'\d+', text)

    if len(text)==4:
        if int(text[0]) + int(text[1]) == int(text[2]):
            net_electors_male,net_electors_female,net_electors_third_gender,net_electors_total = text[0],text[1],"0",text[2]
        elif int(text[0]) + int(text[1]) == int(text[3]):
            net_electors_male,net_electors_female,net_electors_third_gender,net_electors_total = text[0],text[1],"0",text[3]
        else:
            net_electors_male,net_electors_female,net_electors_third_gender,net_electors_total = text[0],text[1],text[2],text[3]
    elif len(text) == 3 and int(text[2])>=int(text[1]) and int(text[2])>=int(text[0]):
        net_electors_male,net_electors_female,net_electors_third_gender,net_electors_total = text[0],text[1],"0",text[2]
    elif len(text) == 2 and int(text[0])*2-100<int(text[1]):
        net_electors_male,net_electors_female,net_electors_third_gender,net_electors_total = text[0],int(text[1])-int(text[0]),"0",text[1]
    else:
        net_electors_male,net_electors_female,net_electors_third_gender,net_electors_total = "","","",""
    
    return net_electors_male,net_electors_female,net_electors_third_gender,net_electors_total


def split_data(data, seps):
    
    for s in seps:
        
        if s in data:
            break
    
    data = data.split(s)

    if len(data)>1:
        data = data[-1].strip()
        return data
    else:
        data = ""
        return data
    
def extract_first_page_details(path):

    img = Image.open(path)
    crop_path = input_images_blocks_path+"page/"
    create_path(crop_path)
    
    a,b,c,d = 3196,314,600,191 # part no
    crop_img = crop_section(a,b,c,d,img)
    
    crop_part_path = crop_path+"part.jpg"
    crop_img.save(crop_part_path)
    crop_img.close()

    text = (pytesseract.image_to_string(crop_part_path, config='--psm 6', lang='eng+pan')) #config='--psm 4' config='-c preserve_interword_spaces=1'
    text = re.findall(r'\d+', text)
    
    if len(text)>0:
        part_no = text[0]
    else:
        part_no = ""
            
    a,b,c,d = 1740,5114,2063,142  # stats for male and female
    crop_img = crop_section(a,b,c,d,img)

    crop_path = input_images_blocks_path+"page/"
    create_path(crop_path)
    
    crop_stat_path = crop_path+"stat.jpg"
    crop_img.save(crop_stat_path)
    crop_img.close()

    a_n,b_n,c_n,d_n = extract_4_numbers(crop_stat_path)
    
    a,b,c,d = 2873,2615,1011,1264  # mandal block
    crop_img = crop_section(a,b,c,d,img)
    
    crop_det_path = crop_path+"det.jpg"
    crop_img.save(crop_det_path)
    crop_img.close()

    text = (pytesseract.image_to_string(crop_det_path, config='--psm 6', lang='pan')) #config='--psm 4' config='-c preserve_interword_spaces=1'
    text = text.split('\n')
    text = [ i for i in text if i!='' and i!='\x0c']
    
    main_town,revenue_division,police_station,mandal,district,pin_code = "","","","","",""
    
    if len(text) == 8:
        
        main_town = text[0]
        revenue_division = text[2]
        police_station = text[3]
        mandal = text[5]
        district = text[6]
        pin_code =text[7]
    elif len(text) == 9:
        
        main_town = text[0]
        revenue_division = text[3]
        police_station = text[4]
        mandal = text[6]
        district = text[7]
        pin_code =text[8]
    elif len(text) == 7:
        
        main_town = text[0]
        revenue_division = text[2]
        police_station = text[3]
        mandal = text[4]
        district = text[5]
        pin_code =text[6]
        
    elif len(text) == 6:
        
        main_town = text[0]
        revenue_division = ""
        police_station = text[2]
        mandal = text[3]
        district = text[4]
        pin_code =text[5]
       

    a,b,c,d = 192,4100,2208,418 # police name name and address
    crop_img = crop_section(a,b,c,d,img)
    
    crop_police_path = crop_path+"police.jpg"
    crop_img.save(crop_police_path)
    crop_img.close()

    text = (pytesseract.image_to_string(crop_police_path, config='--psm 6', lang='pan')) #config='--psm 4' config='-c preserve_interword_spaces=1'
    text = text.split('\n')
    text = [ i for i in text if i!='' and i!='\x0c']
    
    polling_station_name, polling_station_address = "",""
    

    seps = [":","ਪਤਾ “","ਪਤਾ"]
    if len(text) == 2:
        polling_station_name, polling_station_address = split_data(text[0],[":"]),split_data(text[1],seps)
    elif len(text)>=3:
        polling_station_name, polling_station_address = split_data(text[0],[":"]),split_data(text[1],seps)
    
   
    a,b,c,d = 172,321,2900,519 # ac name and parl
    crop_img = crop_section(a,b,c,d,img)
    
    crop_ac_path = crop_path+"ac.jpg"
    crop_img.save(crop_ac_path)
    crop_img.close()

    text = (pytesseract.image_to_string(crop_ac_path, config='--psm 6', lang='pan')) #config='--psm 4' config='-c preserve_interword_spaces=1'
    text = text.split('\n')
    text = [ i for i in text if i!='' and i!='\x0c']
    
    ac_name, parl_constituency = "",""
    seps = [":",";","ਸਥਿਤੀ","ਮਾ", 'ਰੀ']

    if len(text) == 4:
        ac_name = split_data(text[1],seps)
        
        parl_constituency = text[2].split("ਹੈ,")
        if len(parl_constituency)>1:
            parl_constituency = parl_constituency[1].strip()
    elif len(text) == 5:
        ac_name = split_data(text[1],seps)
        parl_constituency = text[3].strip()
    
    elif len(text) == 2:
        parl_constituency = text[0].split("ਹੈ,")
        if len(parl_constituency)>1:
            parl_constituency = parl_constituency[1].strip()
        

   
    return [ac_name,parl_constituency,part_no,main_town,police_station,polling_station_name,polling_station_address,revenue_division,mandal,district,pin_code,a_n,b_n,c_n,d_n]


def arrange_columns(first_page_list,block_list,filename):
    
    year = 2018
    state = 'Punjab'
    
    ac_name,parl_constituency,part_no,main_town,police_station,polling_station_name,polling_station_address,revenue_division,mandal,district,pin_code,net_electors_male,net_electors_female,net_electors_third_gender,net_electors_total = first_page_list
    name,rel_name,rel_type,house_no,age,gender,voter_id,number = block_list
    
    final_list = [number,voter_id,name,rel_name,rel_type,house_no,age,gender,ac_name,
                 parl_constituency,part_no,year,state,filename,main_town,police_station,mandal,
                 revenue_division,district,pin_code,polling_station_name,polling_station_address,
                 net_electors_male,net_electors_female,net_electors_third_gender,net_electors_total]
    
    
    return final_list



def generate_poll_blocks_from_page(page_full_path,page_blocks_path,amend_page):
    
    img = Image.open(page_full_path)
    
    amend = False
    
    def generate(intial_width,a,b,gap):
        count = 0
        crop_width = 1290
        crop_height = 495

        for col in range(1,11):

            for row in range(1,4):
                c = a+crop_width
                d = b+crop_height
                area = (a, b, c, d)
                cropped_img = img.crop(area)
                count = count+1
                
                new_area = (900,100, 1300, 470)
                
                region = Image.new("RGB", (400, 370), (255, 255, 255))
                cropped_img.paste(region,new_area)
                
                cropped_img.save(page_blocks_path+str(count)+".jpg")
                cropped_img.close()

                a = c

            a = intial_width
            b = b+crop_height+gap
    
    page_type,intial_height = check_page_type(img,amend_page)
    
    if page_type == 1:
        intial_width = 130
        generate(intial_width,intial_width,intial_height,6)
        amend_page = False
   
    return amend_page

def check_page_type(img,amend_page):
    
    return 1,393
    

def extract_name(name):
    
    seps = [":","!","-","ਨਾਮ"]
    name = split_data(name,seps)
    
    return name
    
def extract_vid(v_id):
    
    seps = ["|", "_","~","=","-","}"]
    for s in seps:
        v_id = v_id.replace(s,"")
    
    row = v_id.split(" ")
    
    if len(row) == 1:
        return "",row[0]
    elif len(row)==2:
        number = re.findall(r'\d+', row[0].strip())
        if len(number)>0:
            return number[0],row[1]
        else:
            return "",row[1]
    
    elif len(row)>2:
        
        number = re.findall(r'\d+', row[0].strip())
        if len(number)>0:
            return number[0],row[1]+" "+row[2]
        else:
            return "",row[1]+" "+row[2]  
    else:
        return "",v_id

def extract_house_no(house_no):
    seps = [":","ਮਕਾਨਨੰ.","ਮਕਾਨਨੰ","."]
    house_no = split_data(house_no,seps)
    
    if house_no == "":
        house_no = re.findall(r'\d+', house_no)
        if len(house_no)>0:
            return house_no[0]
        else:
            return ""
        
    return house_no
    
def extract_age_gender(age_gender):
    
    age =  re.findall(r'\d+', age_gender)
    
    if len(age)>0:
        age =  age[0]
    else:
        age = ""
    
    if age == "":
        row = age_gender.split(":")
        if len(row)>1:
            row = row[1]
            age =  re.findall(r'\d+', row)
    
            if len(age)>0:
                age =  age[0]
            else:
                age = ""
    
    
    if "ਪੁਰਸ਼" in age_gender:
        gender = "Male"
    elif "ਇਸਤਰੀ" in age_gender:
        gender = "Female"
    else:
        gender = "Male"

    return age, gender

def extract_rel_name(rel_name):
    
    seps = [":","-","ਪਿਤਾ","ਪਤੀ"]
    
    name = split_data(rel_name, seps)
    rel_type = extract_rel_type(rel_name)
           
    return name,rel_type
    
def extract_rel_type(rel_type):

    if "ਪਿਤਾ" in rel_type:
        rel_type = 'father'
        
    elif "ਪਤੀ" in rel_type:
        rel_type = 'husband'
        
    else:
        rel_type = "father"
    
    return rel_type 


def extract_details_from_block(block):
    
    v_id = block[0]
    name = block[1]
    rel_name = block[2]
    house_no = block[3]
    age_gender = block[4]
    
    name = extract_name(name)
    rel_name,rel_type = extract_rel_name(rel_name)
    house_no = extract_house_no(house_no)
    age, gender = extract_age_gender(age_gender)
    number,voter_id = extract_vid(v_id)
    
    return [name,rel_name,rel_type,house_no,age,gender,voter_id,number]

def run_tesseract(path):
    text = (pytesseract.image_to_string(path, config='--psm 6', lang='pan'))
    params_list = text.split('\n')
    new_params_list = [ i for i in params_list if i!='' and i!='\x0c']

    return new_params_list

def pdf_process(pdf_file_name):

    begin_time = time.time()
    
    print(pdf_file_name, datetime.now().strftime('%Y/%m/%d %H:%M:%S'))

    if not pdf_file_name.endswith(".pdf"):
        return pdf_file_name, 0

    try:        
        #create images,blocks and csvs paths for each file
        pdf_file_name_without_ext = pdf_file_name.split('.pdf')[0]
        input_pdf_images_path = PARSE_DATA_PAGES+pdf_file_name_without_ext+"/"
        create_path(input_pdf_images_path)
        
        input_images_blocks_path = PARSE_DATA_BLOCKS+pdf_file_name_without_ext+"/"
        create_path(input_images_blocks_path)
        
        if os.path.exists(PARSE_DATA_CSVS+pdf_file_name_without_ext+".csv"):
            print(pdf_file_name_without_ext+".csv", "already exists")
            continue
        
        #convert pdf into bunch of images
        pdf_2_images_list = pdf_to_img(state_pdfs_path+pdf_file_name, input_pdf_images_path,dpi=500)

        
        #sort pages for looping
        input_images = os.listdir(input_pdf_images_path)
        sort_nicely(input_images)
        
        #empty intial data
        df = pd.DataFrame(columns = COLUMNS)
        order_problem = []
            
        amend_page = False
                   
        #for each page, parse the data
        for page in input_images:
            
            page_full_path = input_pdf_images_path+page
            
            #extract first page content
            if page == '1.jpg':
                first_page_list = extract_first_page_details(page_full_path)
                continue

            #ingnore 2nd page and last page
            if page == '2.jpg' or input_images[-1] == page:
                continue

            #loop from 3 page onwards
            if page.endswith('.jpg'):
                
                final_invidual_blocks = []
                blocks_path = input_images_blocks_path+"blocks/"
                create_path(blocks_path)

                page_idx = page.split(".jpg")[0] + "/"
                page_blocks_path = blocks_path+page_idx
                create_path(page_blocks_path)
                            
                generate_poll_blocks_from_page(page_full_path,page_blocks_path,amend_page)
                
                sorted_blocks = os.listdir(page_blocks_path)
                sort_nicely(sorted_blocks)
                
                for jpg_file in sorted_blocks:
                    
                    if jpg_file.endswith('.jpg') :
 
                        new_params_list = run_tesseract(page_blocks_path+jpg_file)

                        if len(new_params_list)==5:
                            final_invidual_blocks.append(new_params_list)
                        else:
                            order_problem.append((page, jpg_file,new_params_list))

            #put the data into dataframe
            for block in final_invidual_blocks:

                block_list = extract_details_from_block(block)
                final_list = arrange_columns(first_page_list,block_list,pdf_file_name_without_ext)

                df_length = len(df)
                df.loc[df_length] = final_list
                
            print("page done", page)

        #save the dataframe(pdf) data into csv
        save_to_csv(df,PARSE_DATA_CSVS+pdf_file_name_without_ext+".csv")
        print("CSV saved",pdf_file_name_without_ext)

    except Exception as e:
        print('ERROR:', e, pdf_file_name_without_ext)
        traceback.print_exc()
    finally:
        print("Clean up working files...")
        shutil.rmtree(input_pdf_images_path, ignore_errors=True)
        shutil.rmtree(input_images_blocks_path, ignore_errors=True)

    end_time = time.time()

    return pdf_file_name_without_ext, end_time - begin_time


if __name__ == '__main__':

    print('Tesseract Version:', pytesseract.get_tesseract_version())
    print('multiprocessing cpu_count:', multiprocessing.cpu_count())
    print('os cpu_count:', os.cpu_count())
    print('sched_getaffinity:', len(os.sched_getaffinity(0)))

    #a_pool = multiprocessing.Pool(multiprocessing.cpu_count())
    #results = a_pool.map(pdf_process, state_pdfs_files)

    with MPIPoolExecutor() as executor:
        results = executor.map(pdf_process, state_pdfs_files)
        for res in results:
            print(res)

    #combine all state files into one csv
    #combine_all_csvs("punjab_final.csv",PARSE_DATA_CSVS)