Update app.py

app.py

@@ -4,81 +4,74 @@ import numpy as np
 import csv
 from datetime import datetime
 
-# video_capture=cv2.VideoCapture(1)
-# if not video_capture.isOpened():
-#     print("Failed to open the video capture.")
-#     exit()
+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
 
-sir_image=face_recognition.load_image_file("photos/sir.jpeg")
-sir_encoding=face_recognition.face_encodings(sir_image)[0]
+now = datetime.now()
+current_date = now.strftime("%Y-%m-%d")
 
-vikas_image=face_recognition.load_image_file("photos/vikas.jpg")
-vikas_encoding=face_recognition.face_encodings(vikas_image)[0]
+f = open(current_date + '.csv', 'w+', newline='')
+lnwriter = csv.writer(f)
 
-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)
-
-############################
 import io
 import streamlit as st
-bytes_data=None
-
-run=st.checkbox('Run')
-FRAME_WINDOW=st.image([])
-camera=cv2.VideoCapture(0)
-
- 
 
+bytes_data = None
 
+run = st.checkbox('Run')
+FRAME_WINDOW = st.image([])
+camera = cv2.VideoCapture(0)
 
 while run:
-    _,frame=camera.read()
-    frame=cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
-    # FRAME_WINDOW.image(frame)
-    small_frame=cv2.resize(frame,(0,0),fx=0.25,fy=0.25)
-    rgb_small_frame=small_frame[:,:,::-1]
+    _, frame = camera.read()
+    
+    if frame is None:
+        continue
+    
+    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+    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_locations = face_recognition.face_locations(rgb_small_frame)
         face_encodings = face_recognition.face_encodings(small_frame, face_locations)
-        face_names=[]
+        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)
+            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]
+                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'):
+                    current_time = now.strftime("%H-%M-%S")
+                    lnwriter.writerow([name, current_time, "Present"])
+    
+    cv2.imshow("attendance system", frame)
+    
+    if cv2.waitKey(1) & 0xFF == ord('q'):
         break
-else:
-    st.write('Stopped')
-f.close()
+    else:
+        st.write('Stopped')
+        
+f.close()