import cv2 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() 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()