code: import weaviate
  import cv2
  import os,sys
  import pandas as pd
  from student_test import getFaces, testImage, testit
  
  def markAttendance(faces,own=False):
      '''
      This function takes in a list of image paths (paths of face images)
      and then uses weaviate's image2vec-neural module to classify
      each image depending upon the images initially uploaded to weaviate.
      It then classifies the image (ie identifies the student) and marks their attendance.
      '''
      data = pd.DataFrame(columns=['Name','Present'])
      for img in faces:
      
          if own:
              name = testit(img)
          else:
              name = testImage({"image":"{}".format(img)})
          #print(name)
          dict = {"Name":name,"Present":'P'}
          data = data.append(dict,ignore_index=True)
      print(data)
      return data
apis: pandas.DataFrame