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40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
import face_model
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import argparse
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import cv2
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import sys
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import numpy as np
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import datetime
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parser = argparse.ArgumentParser(description='face model test')
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# general
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parser.add_argument('--image-size', default='112,112', help='')
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parser.add_argument('--image', default='Tom_Hanks_54745.png', help='')
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parser.add_argument('--model',
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default='model/model,0',
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help='path to load model.')
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parser.add_argument('--gpu', default=0, type=int, help='gpu id')
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parser.add_argument(
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'--det',
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default=0,
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type=int,
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help='mtcnn option, 1 means using R+O, 0 means detect from begining')
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args = parser.parse_args()
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model = face_model.FaceModel(args)
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#img = cv2.imread('Tom_Hanks_54745.png')
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img = cv2.imread(args.image)
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img = model.get_input(img)
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#f1 = model.get_feature(img)
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#print(f1[0:10])
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for _ in range(5):
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gender, age = model.get_ga(img)
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time_now = datetime.datetime.now()
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count = 200
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for _ in range(count):
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gender, age = model.get_ga(img)
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time_now2 = datetime.datetime.now()
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diff = time_now2 - time_now
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print('time cost', diff.total_seconds() / count)
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print('gender is', gender)
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print('age is', age)
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