# import cv2
# import time
# import numpy as np

# import pickle
# from face_recognition import face_locations, face_encodings, compare_faces, face_distance

# folderpath="/home/swadhin/GitHubproject/liveattendence_with_anti_cheat/backend/app/functions/pictures/222156259.jpeg"

# pic=cv2.imread(folderpath)
# pic=cv2.resize(pic,(0,0),None,0.25,0.25)
# encode=face_encodings(pic)[0]
# studentIds = ['222156259']
# encodelist=[]
# encodelist.append(encode)
# incodelistnown=[encodelist,studentIds]
# file=open('EncodeFile.p','wb')
# pickle.dump(incodelistnown,file)
# file.close()    


# cap = cv2.VideoCapture("https://192.168.0.100:8080/video")
# cap.set(3, 640)
# cap.set(4, 480)

# file = open('EncodeFile.p', 'rb')
# encodeListKnownWithIds = pickle.load(file)

# encodeListKnown, studentIds = encodeListKnownWithIds


# while True:
#     success, img = cap.read()
#     imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25)
#     imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
#     faceCurFrame = face_locations(imgS)
#     encodeCurFrame =face_encodings(imgS, faceCurFrame)
#     if faceCurFrame:
#         for encodeFace, faceLoc in zip(encodeCurFrame, faceCurFrame):
#             matches = compare_faces(encodeListKnown, encodeFace)
#             faceDis = face_distance(encodeListKnown, encodeFace)
#             matchIndex = np.argmin(faceDis)
#             if matches[matchIndex]:
#                 y1, x2, y2, x1 = faceLoc
#                 y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
#                 bbox = 55 + x1, 162 + y1, x2 - x1, y2 - y1
#                 cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
#                 cv2.rectangle(img, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)
#                 cv2.putText(img, studentIds[matchIndex], (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
#     cv2.imshow('Webcam', img)
#     if cv2.waitKey(1) & 0xFF == ord('q'):
#         break
# cap.release()

# cv2.destroyAllWindows()



test={
    "hello":"world",
}
x=list(test.keys())[0]
print(x)