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trinityzhub/face_recognizer.py

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Created February 2, 2023 21:18
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  1. @ahmetozlu ahmetozlu revised this gist Sep 30, 2017. No changes.
  2. @ahmetozlu ahmetozlu created this gist Sep 30, 2017.
    89 changes: 89 additions & 0 deletions face_recognizer.py
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    #----------------------------------------------
    #--- Author : Ahmet Ozlu
    #--- Mail : [email protected]
    #--- Date : 21st September 2017
    #----------------------------------------------

    import face_recognition
    import cv2
    import os
    import create_csv

    # Open the input movie file
    input_movie = cv2.VideoCapture("tbbt.mp4")
    length = int(input_movie.get(cv2.CAP_PROP_FRAME_COUNT))

    # Load some sample pictures and learn how to recognize them.
    lmm_image = face_recognition.load_image_file("sheldon.jpg")
    lmm_face_encoding = face_recognition.face_encodings(lmm_image)[0]

    al_image = face_recognition.load_image_file("penny.jpg")
    al_face_encoding = face_recognition.face_encodings(al_image)[0]

    known_faces = [
    lmm_face_encoding,
    al_face_encoding
    ]

    # Initialize some variables
    face_locations = []
    face_encodings = []
    face_names = []
    frame_number = 0

    current_path = os.getcwd()

    counter = 0
    counter1 = 0

    while True:
    # Grab a single frame of video
    ret, frame = input_movie.read()
    frame_number += 1

    # Quit when the input video file ends
    if not ret:
    break

    # Find all the faces and face encodings in the current frame of video
    face_locations = face_recognition.face_locations(frame)
    face_encodings = face_recognition.face_encodings(frame, face_locations)

    face_names = []
    for face_encoding in face_encodings:
    # See if the face is a match for the known face(s)
    match = face_recognition.compare_faces(known_faces, face_encoding, tolerance=0.50)

    # If you had more than 2 faces, you could make this logic a lot prettier
    # but I kept it simple for the demo
    name = None
    if match[0]:
    name = "Sheldon Cooper"
    elif match[1]:
    name = "Penny"

    face_names.append(name)

    # Label the results
    for (top, right, bottom, left), name in zip(face_locations, face_names):
    if not name:
    continue

    # Draw a box around the face
    cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

    crop_img = frame[top:bottom, left:right]
    if(name == "Sheldon Cooper"):
    cv2.imwrite(current_path + "/face_database/Sheldon/" + "sheldon"+str(counter)+".png",crop_img)
    counter = counter + 1
    elif(name == "Penny"):
    cv2.imwrite(current_path + "/face_database/Penny/" + "penny"+str(counter1)+".png",crop_img)
    counter1 = counter1 + 1

    # Write the resulting image to the output video file
    print("Writing frame {} / {}".format(frame_number, length))

    # All done!
    input_movie.release()
    cv2.destroyAllWindows()
    create_csv.CreateCsv(current_path + "/face_database/")