先安装依赖库dlib、face_recognition、cv2

下载wheel文件：

python3.6：

dlib-19.7.0-cp36-cp36m-win_amd64.whl: https://drfs.ctcontents.com/file/1445568/768652503/68cb5d/Python/dlib-19.7.0-cp36-cp36m-win_amd64.whl

python3.7:

dlib-19.17.99-cp37-cp37m-win_amd64.whl: https://drfs.ctcontents.com/file/1445568/768652504/b726a5/Python/dlib-19.17.99-cp37-cp37m-win_amd64.whl

python3.8:

dlib-19.19.0-cp38-cp38-win_amd64.whl.whl: https://drfs.ctcontents.com/file/1445568/768652508/77e657/Python/dlib-19.19.0-cp38-cp38-win_amd64.whl.whl

再使用pip安装face_recognition、cv2

   

    

     

      

     
     

      

       pip install opencv-python
      
     
    

     

      

     
     

      

       pip install face-recognition
      
     
   

比较两张图片

   

    

     

      

     
     

      

       import cv2
      
     
    

     

      

     
     

      

       import face_recognition
      
     
    

     

      

     
     

      
 
      
     
    

     

      

     
     

      

       def find_face_encodings(image_path):
      
     
    

     

      

     
     

      

           # reading image
      
     
    

     

      

     
     

      

           image = cv2.imread(image_path)
      
     
    

     

      

     
     

      
    
      
     
    

     

      

     
     

      

           # get face encodings from the image
      
     
    

     

      

     
     

      

           face_enc = face_recognition.face_encodings(image)
      
     
    

     

      

     
     

      
    
      
     
    

     

      

     
     

      

           # return face encodings
      
     
    

     

      

     
     

      

           return face_enc[0]
      
     
    

     

      

     
     

      
 
      
     
    

     

      

     
     

      

       # getting face encodings for first image
      
     
    

     

      

     
     

      

       image_1 = find_face_encodings("image_1.png")
      
     
    

     

      

     
     

      
 
      
     
    

     

      

     
     

      

       # getting face encodings for second image
      
     
    

     

      

     
     

      

       image_2  = find_face_encodings("image_2.png")
      
     
    

     

      

     
     

      
 
      
     
    

     

      

     
     

      

       # checking both images are same
      
     
    

     

      

     
     

      

       is_same = face_recognition.compare_faces([image_1], image_2)[0]
      
     
    

     

      

     
     

      

       print(f"Is Same: {is_same}")
      
     
    

     

      

     
     

      

       if is_same:
      
     
    

     

      

     
     

      

           # finding the distance level between images
      
     
    

     

      

     
     

      

           distance = face_recognition.face_distance([image_1], image_2)
      
     
    

     

      

     
     

      

           distance = round(distance[0] * 100)
      
     
    

     

      

     
     

      
    
      
     
    

     

      

     
     

      

           # calcuating accuracy level between images
      
     
    

     

      

     
     

      

           accuracy = 100 - round(distance)
      
     
    

     

      

     
     

      
    
      
     
    

     

      

     
     

      

           print("The images are same")
      
     
    

     

      

     
     

      

           print(f"Accuracy Level: {accuracy}%")
      
     
    

     

      

     
     

      

       else:
      
     
    

     

      

     
     

      

           print("The images are not same")
      
     
   
  

   
  

输出：

Is Same: True

The images are same

Accuracy Level: 70%