42 lines
1.7 KiB
Python
42 lines
1.7 KiB
Python
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import DBHelper
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import Facial_Recognition_Registration
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import Facial_Recognition_Enrollment
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from joblib import Parallel, delayed
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import multiprocessing
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def update_your_face(firstname, lastname, email, phone):
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# Determines user ID before adding the data to the database.
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# User ID is determined from number of user dataset in database
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# Later on it starts face recognition system and uploads it into the database based on the given user ID.
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users = DBHelper.db.child("Users").get()
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print("Updating the User information...")
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try:
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count = 0
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for user in users.each():
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count += 1
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if DBHelper.get_email("User_" + str(count)) == email:
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break
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print("Face registration start...")
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Facial_Recognition_Registration.register_your_face("User_" + str(count))
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Parallel(n_jobs=multiprocessing.cpu_count())(delayed(update_parallel_user_photos)(i, count) for i in range(50))
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DBHelper.upload_data("User_" + str(count), firstname, lastname, email, phone)
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print("Data saved! Starting enrollment...")
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Facial_Recognition_Enrollment.enroll_face_dataset()
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print("Face registration completed!")
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print("Success.")
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except:
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print("It seems there is no user registered.")
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def update_parallel_user_photos(i, count):
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DBHelper.delete_user_photo("User_" + str(count) + "/" + str(i) + ".jpg")
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DBHelper.upload_user_photo("User_" + str(count) + "/" + str(i) + ".jpg")
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if __name__ == "__main__":
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f = input('Enter your First Name:')
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l = input('Enter your Last Name:')
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e = input('Enter your E-Mail:')
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p = input('Enter your Phone:')
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update_your_face(f, l, e, p)
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