Recognising Face using the "face_recognition" library

recognising_face.py

import face_recognition

# Number of known persons
n = 2

# Create a list of all known face encodings
known_face_encodings = []
for num in range(1, n + 1):
  image_file = f"known_person_{num}.jpg"
  # Load each known image
  image_of_person = face_recognition.load_image_file(image_file)
  # Get the face encoding of each person. This can fail if no one is found in the photo
  face_encoding = face_recognition.face_encodings(image_of_person)[0]
  # Create a list of all known face encodings
  known_face_encodings.append(face_encoding)

# Load the image we want to check
unknown_image = face_recognition.load_image_file(
  "test_image.jpg"
)

# Get face encodings for any people in the picture
unknown_face_encodings = face_recognition.face_encodings(
  unknown_image
)

# There might be more than one person in the photo, so we need to loop over each face we found
for unknown_face_encoding in unknown_face_encodings:
  face_distances = face_recognition.face_distance(
    known_face_encodings,
    unknown_face_encoding
  )

  print(f"Distance between unknown image and each known image: {face_distances}")

  # Test if this unknown face encoding matches any of the n people we know
  results = face_recognition.compare_faces(
    known_face_encodings,
    unknown_face_encoding,
    tolerance=0.6
  )

  for num in range(0, n):
    if results[num]:
      print(f"Found Person {num + 1} in the photo!")