text: from minio import Minio
  import os 
  import argparse
  import numpy as np 
  import cv2
  import glob
  import json
  
  from refer.utils import CreateExel
  from refer.utils import createFolder
  from refer.utils import print_progress
  
  # Argument  
  
  parser = argparse.ArgumentParser(description="Convert the Data")
  parser.add_argument('--base', '--b', help = 'the base address of the data')
  args = parser.parse_args()
  
  Basic = args.base
  Basic = os.path.abspath(Basic)
  
  def convert2line (Basic, folder): 
  
      # The Address
  
      Input_Address = os.path.join(Basic, folder)
      Input_Address = os.path.abspath(Input_Address)
      print('Input Address is ' + Input_Address)
  
      M_folder = "M_" + folder
      Mask_Address = Basic + M_folder
      Mask_Address = os.path.join(Basic, M_folder)
      Mask_Address = os.path.abspath(Mask_Address)
      print('Address of Masked file is ' + Mask_Address)
      createFolder(Mask_Address)
  
      # Arrange the file
  
      text_storage=[]
      image_storage=[]
  
      for name in sorted(glob.glob(Input_Address + '/*.json')):
          text_storage.append(name) 
   
      for name in sorted(glob.glob(Input_Address + '/*.BMP')):
          image_storage.append(name) 
  
      # Convert
  
      i=0
      print_progress(i,len(text_storage))
  
      j=0
      for j in range(len(text_storage)):
  
  
          # Step 1. Read the image   
          img = cv2.imread(image_storage[j]) 
          (a,b,c)=img.shape
          name1 = image_storage[j]
          sub1 = Input_Address
          sub2 ="/"
          name2 = name1.replace(sub1, '')
          fname = name2.replace(sub2, '')
  
          # Step 2. 
  
          text = open(text_storage[j])
          data = json.load(text)
          pts = data ["one"]
  
          size = np.array([b,a])
          pts = (pts*size).astype(int)
  
          # Step 3. Generate Mask 
          img=np.zeros((a,b))
          Mask = cv2.fillPoly(img, [pts], 1)
          Mask = np.array(Mask)
          os.chdir(Mask_Address) 
          cv2.imwrite(fname, Mask)     
  
          i += 1
          print_progress(i,len(text_storage))
  
      # Remove the json file 
  
      for name in sorted(glob.glob(Input_Address + '/*.json')):
          os.remove(name)
  
  # Download & Convert
  
  folder_name = ['tests', 'train', 'valid']
  
  for folder in folder_name:      
  
      # Convert
  
      print ("Converting the file")
      convert2line (Basic = Basic , folder = folder) 