# getting wrong cosine similarity when using face_recognition.faceencodings

I am trying to calculate cosine similarity between two face encodings returned by face_Recognition.face encoding() which 128d vector which always is above 0.8 also is the face encoding normalized already or is it not? because I feel like that might be causing the issue

this are the function I used to get

def get_encodings(face):

return face_recognition.face_encodings(face, model="large")[0]

def cosine_similarity(encodings):
if len(encodings) < 2:
return 0
normalized_encodings = [enc / np.linalg.norm(enc) for enc in encodings]
return round(np.dot(normalized_encodings[0], normalized_encodings[1]), 2)