self.input_size = (128, 128)
def get_feature(self, img):
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img = cv2.resize(img, self.input_size, interpolation=cv2.INTER_AREA)
blob = cv2.dnn.blobFromImage(img, scalefactor=1 / 127.5, mean=127.5)
self.model.setInput(blob)
output = self.model.forward(['output'])
return output
if __name__ == '__main__':
from yoloface_detect_align_module import yoloface ###你还可以选择其他的人脸检测器
device = 'cuda' if torch.cuda.is_available() else 'cpu'
# face_embdnet = arcface(device=device)
face_embdnet = arcface_dnn() ###已调试通过，与pytorch版本的输出结果吻合
detect_face = yoloface(device=device)
out_emb_path = 'yoloface_detect_arcface_feature.pkl'
imgroot = '你的文件夹绝对路径'
dirlist = os.listdir(imgroot) ### imgroot里有多个文件夹，每个文件夹存放着一个人物的多个肖像照，文件夹名称是人名
feature_list, name_list = [], []
for i,name in enumerate(dirlist):
sys.stdout.write("\rRun person{0}, name:{1}".format(i, name))
sys.stdout.flush()
imgdir = os.path.join(imgroot, name)
imglist = os.listdir(imgdir)
for imgname in imglist:
srcimg = cv2.imread(os.path.join(imgdir, imgname))
_, face_img = detect_face.detect(srcimg) ###肖像照，图片中有且仅有有一个人脸
if len(face_img)!=1:
var_name for var_name, var_val in callers_local_vars if var_val is var
]
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description='Object Detection using YOLO in OPENCV')
parser.add_argument('--imgpath',
type=str,
default='s_l.jpg',
help='Path to image file.')
args = parser.parse_args()
device = 'cuda' if torch.cuda.is_available() else 'cpu'
align = False
yoloface_detect = yoloface(device=device, align=align)
ultraface_detect = ultraface()
ssdface_detect = ssdface()
retinaface_detect = retinaface(device=device, align=align)
retinaface_dnn_detect = retinaface_dnn(align=align)
mtcnn_detect = mtcnnface(device=device, align=align)
facebox_detect = facebox(device=device)
facebox_dnn_detect = facebox_dnn()
dbface_detect = dbface(device=device, align=align)
centerface_detect = centerface(align=align)
lffdface_detect = lffdface(version=1)
libface_detect = libfacedet(align=align)
srcimg = cv2.imread(args.imgpath)
a = time.time()
