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