・　pip install opencv-python
　・　pip install deepface
　・　pip install tensorflow==2.12.0
　・　pip3 install mecab-python3
　・　pip install psutil
　・　pip install dlib
　・　pip install ultralytics
　・　pip install facenet-pytorch
　・　pip install mediapipe

#coding: utf-8
# ////////////////////////////////////////////////////////////////////////////
# ///【DeepFace・顔認証(Facial Verification)】
# ////////////////////////////////////////////////////////////////////////////
if "__file__" in globals():
    import os, sys
    sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
    sys.path.append(os.path.join(os.path.dirname(__file__), "..") + "//..//")
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
from DeZero.common.nlp_util import *
import cv2
from deepface import DeepFace
tensorflow_warning_cancel()

if __name__ == "__main__":
    img1_path = "c:\\Photo\\aragaki.jpg"
    img2_path = "c:\\Photo\\aragaki-2.jpg"

    # /// 顔認識モデル(models)
    # ////////////////////////////////////////////////////////////////////////////
    models = [
      "VGG-Face",
      "Facenet",
      "Facenet512",
      "OpenFace",
      "DeepFace",
      "DeepID",
      "ArcFace",
      "Dlib",
      "SFace",
    ]

    # /// バックエンド(backends)
    # ////////////////////////////////////////////////////////////////////////////
    backends = [
      'opencv',
      'ssd',
      'dlib',
      'mtcnn',
      'retinaface',
      'mediapipe',
      'yolov8',
      'yunet',
      'fastmtcnn'
    ]

    # /// 類似度(metrics)
    # ////////////////////////////////////////////////////////////////////////////
    metrics = ["cosine", "euclidean", "euclidean_l2"]

    # /// 正規化(normalizations)
    # ////////////////////////////////////////////////////////////////////////////
    normalizations = ["base", "raw", "Facenet", "Facenet2018", "VGGFace", "VGGFace2", "ArcFace"]

    for model  in models:
        for backend  in backends:
            for metric  in metrics:
                for normalization  in normalizations:
                    print("\n",model,",",backend,",",metric,",",normalization,",",end="")
                    # /// 顔比較(face verification) tensorflow=2.16.1(失敗)→2.15.0
                    # ////////////////////////////////////////////////////////////////////////////
                    verification = DeepFace.verify(
                        img1_path=img1_path,                        # img1_path: Union[str, np.ndarray, List[float]]
                        img2_path=img2_path,                        # img2_path: Union[str, np.ndarray, List[float]]
                        model_name=model,                           # model_name: str = "VGG-Face"
                        detector_backend = backend,                 # detector_backend: str = "opencv"
                        distance_metric=metric,                     # distance_metric: str = "cosine"
                        enforce_detection=False,                    # enforce_detection: bool = True
                        align=True,                                 # align: bool = True
                        expand_percentage= 0,                       # expand_percentage: int = 0
                        normalization=normalization,                # normalization: str = "base"
                        silent=False                                # silent: bool = False
                    )
                    print(verification['verified'],",",verification['time'],",",verification['distance'],",",verification['threshold'],",",verification['facial_areas'])

# [result]
#  VGG-Face , opencv , cosine , base ,True , 2.86 , 0.6333374542244692 , 0.68 , {'img1': {'x': 102, 'y': 75, 'w': 276, 'h': 276, 'left_eye': (86, 100), 'right_eye': (187, 101)}, 'img2': {'x': 151, 'y': 118, 'w': 447, 'h': 447, 'left_eye': (147, 180), 'right_eye': (294, 173)}}
#  VGG-Face , opencv , cosine , raw ,True , 0.42 , 0.6333375914804695 , 0.68 , {'img1': {'x': 102, 'y': 75, 'w': 276, 'h': 276, 'left_eye': (86, 100), 'right_eye': (187, 101)}, 'img2': {'x': 151, 'y': 118, 'w': 447, 'h': 447, 'left_eye': (147, 180), 'right_eye': (294, 173)}}

＜中略＞

# VGG-Face , mtcnn , cosine , base ,
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# True , 2.37 , 0.5685267811552565 , 0.68 , {'img1': {'x': 125, 'y': 75, 'w': 227, 'h': 289, 'left_eye': (188, 174), 'right_eye': (293, 175)}, 'img2': {'x': 198, 'y': 116, 'w': 335, 'h': 439, 'left_eye': (298, 299), 'right_eye': (449, 290)}}