使face_recognition返回最相似人脸下标

在使用face_recognition的过程中发现 compare_faces 比较人脸的过程会将小于 tolerance 的人脸编码全部按照true返回，会丢失具体的欧氏距离的信息，源码如下：

def compare_faces(known_face_encodings, face_encoding_to_check, tolerance=0.6):
    """
    Compare a list of face encodings against a candidate encoding to see if they match.
    :param known_face_encodings: A list of known face encodings
    :param face_encoding_to_check: A single face encoding to compare against the list
    :param tolerance: How much distance between faces to consider it a match. Lower is more strict. 0.6 is typical best performance.
    :return: A list of True/False values indicating which known_face_encodings match the face encoding to check
    """
    return list(face_distance(known_face_encodings, face_encoding_to_check) <= tolerance)

在这里返回的是一个list，长度和传入的known_face_encodings相等

对此进行调整，自己写了一个函数，如下：

# 调整face_recognition的脸部编码比较函数，返回下标和距离最小值
def my_compare_faces(known_face_encodings, face_encoding_to_check, tolerance):
    # 如果已知人脸列表为空或待比较人脸为空则直接返回
    if len(known_face_encodings) == 0 or len(face_encoding_to_check) == 0:
        return -1, 1
    distance = face_recognition.face_distance(known_face_encodings, face_encoding_to_check)
    if distance.min() < tolerance:
        return distance.argmin(), distance.min()
    else:
        return -1, distance.min()

在这里返回人脸距离的小于 tolerance 的最小值的下标，即返回最相似的人脸下标，如果不符合tolerance 就返回-1，对返回值做一个判定即可区分。