employee attendance system using face recognization

# One_Shot_Learning

## Please refer the document attached to this repo
## clone the repository.
## make sure you have face recognization package installed properly inorder to do it you need to have visual studio with c++.
## run requirements.txt and make sure all the packages are installed.
## provide sample images.
## execute the code it will note down attendance automatically to the excel sheet.

Author: sayantann11

attendance-automator/main.py

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+import cv2
+from face_recognition.api import face_encodings
+import numpy as np
+import face_recognition
+import os
+from datetime import datetime
+
+path= 'images'
+
+images=[]
+
+personName=[]
+
+myList=os.listdir(path)
+
+print(myList)
+
+for cu_img in myList:
+    current_Img=cv2.imread(f'{path}/{cu_img}')
+    images.append(current_Img)
+    personName.append(os.path.splitext(cu_img)[0])
+
+print(personName)
+
+
+def faceEncodings(images):
+    encodeList=[]
+
+    for img in images:
+        img=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
+        encode=face_recognition.face_encodings(img)[0]
+        encodeList.append(encode)
+
+    return encodeList
+
+encodeListKnown = (faceEncodings(images))
+
+print("All Encoding Complete!!!!!")
+
+
+def attendance(name):
+    with open('Attendance.csv','r+') as f:
+        myDataList = f.readlines()
+        nameList = []
+        for line in myDataList:
+            entry = line.split(',')
+            nameList.append(entry[0])
+
+        if name not in nameList:
+            time_now = datetime.now()
+            tStr = time_now.strftime('%H:%M:%S')
+            dStr = time_now.strftime('%d/%m/%Y')
+            f.writelines(f'{name},{tStr},{dStr}')
+
+
+cap= cv2.VideoCapture(0)
+
+while True:
+
+    ret,frame = cap.read()
+    faces = cv2.resize(frame,(0,0),None,0.25,0.25)
+    faces= cv2.cvtColor(faces,cv2.COLOR_BGR2RGB)
+
+
+    facesCurrentFrame = face_recognition.face_locations(faces)
+    encodesCurrentFrame = face_recognition.face_encodings(faces,facesCurrentFrame)
+
+
+    for encodeFace,faceLoc in zip(encodesCurrentFrame, facesCurrentFrame):
+        matches = face_recognition.compare_faces(encodeListKnown,encodeFace)
+        faceDis = face_recognition.face_distance(encodeListKnown,encodeFace)
+
+        matchIndex = np.argmin(faceDis)
+
+        if matches[matchIndex]:
+            name = personName[matchIndex].upper()
+            # print(name)
+            y1,x2,y2,x1 = faceLoc 
+
+            y1,x2,y2,x1 = y1*4,x2*4,y2*4,x1*4
+            cv2.rectangle(frame,(x1,y1),(x2,y2),(0,255,0),2)
+            cv2.rectangle(frame,(x1,y2-35),(x2,y2),(0,255,0),cv2.FILLED)
+            cv2.putText(frame,name,(x1+6, y2-6), cv2.FONT_HERSHEY_COMPLEX,1,(255,0,0), 1)
+            attendance(name)
+    cv2.imshow("Camera", frame)
+
+    if cv2.waitKey(10) == 13:
+        break
+
+cap.release()
+
+cv2.destroyAllWindows()