Update app.py

app.py

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+import face_recognition
+import cv2
+import numpy as np
+import csv
+from datetime import datetime
+
+video_capture=cv2.VideoCapture(0)
+
+sir_image=face_recognition.load_image_file("photos/sir.jpeg")
+sir_encoding=face_recognition.face_encodings(sir_image)[0]
+
+vikas_image=face_recognition.load_image_file("photos/vikas.jpg")
+vikas_encoding=face_recognition.face_encodings(vikas_image)[0]
+
+known_face_encoding=[sir_encoding,vikas_encoding]
+
+known_faces_names=["Sarwan Sir","Vikas"]
+
+students=known_faces_names.copy()
+
+face_locations=[]
+face_encodings=[]
+face_names=[]
+s=True
+
+
+
+now=datetime.now()
+current_date=now.strftime("%Y-%m-%d")
+
+
+f=open(current_date+'.csv','w+',newline='')
+lnwriter=csv.writer(f)
+
+while True:
+    _,frame=video_capture.read()
+    small_frame=cv2.resize(frame,(0,0),fx=0.25,fy=0.25)
+    rgb_small_frame=small_frame[:,:,::-1]
+    if s:
+        face_locations=face_recognition.face_locations(rgb_small_frame)
+        face_encodings = face_recognition.face_encodings(small_frame, face_locations)
+        face_names=[]
+        for face_encoding in face_encodings:
+            matches=face_recognition.compare_faces(known_face_encoding,face_encoding)
+            name=""
+            face_distance=face_recognition.face_distance(known_face_encoding,face_encoding)
+            best_match_index=np.argmin(face_distance)
+            if matches[best_match_index]:
+                name=known_faces_names[best_match_index]
+
+            face_names.append(name)
+            if name in known_faces_names:
+                if name in students:
+                    students.remove(name)
+                    print(students)
+                    current_time=now.strftime("%H-%M-%S")
+                    lnwriter.writerow([name,current_time,"Present"])
+    cv2.imshow("attendence system",frame)
+    if cv2.waitKey(1) & 0xFF==ord('q'):
+        break
+video_capture.release()
+cv2.destroyAllWindows()
+f.close()