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test.py
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import face_recognition
import cv2
import numpy as np
import csv
import os
from datetime import datetime
video_capture = cv2.VideoCapture(0);
sahil_image = face_recognition.load_image_file("photos/sahil.jpg")
sahil_encoding = face_recognition.face_encodings(sahil_image)[0]
aman_image = face_recognition.load_image_file("photos/aman.jpg")
aman_encoding = face_recognition.face_encodings(aman_image)[0]
shreyansh_image = face_recognition.load_image_file("photos/shreyansh.jpg")
shreyansh_encoding = face_recognition.face_encodings(shreyansh_image)[0]
amit_rathi_sir_image = face_recognition.load_image_file("photos/amit.jpg")
amit_rathi_sir_encoding = face_recognition.face_encodings(amit_rathi_sir_image)[0]
navaljeet_sir_image = face_recognition.load_image_file("photos/navaljeet.jpg")
navaljeet_sir_encoding = face_recognition.face_encodings(navaljeet_sir_image)[0]
nkjain_sir_image = face_recognition.load_image_file("photos/nkjain.jpg")
nkjain_sir_encoding = face_recognition.face_encodings(nkjain_sir_image)[0]
known_face_encoding = [
sahil_encoding,
shreyansh_encoding,
aman_encoding,
amit_rathi_sir_encoding,
navaljeet_sir_encoding,
nkjain_sir_encoding
]
known_face_names = [
"Sahil Gupta",
"Shreyansh Jaiswal",
"Aman Tripathi",
"Dr. Amit Rathi",
"Dr. Navaljeet Singh Arora",
"Dr. Neelesh Kumar Jain"
]
students = known_face_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(rgb_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_face_names[best_match_index]
face_names.append(name)
if name in known_face_names:
if name in students:
students.remove(name)
print(students)
current_time = now.strftime("%H-%M")
lnwriter.writerow([name,current_time])
cv2.imshow("Attendance System",frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
f.close()