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35 lines
854 B
Python
35 lines
854 B
Python
import cv2
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import numpy as np
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from keras.models import load_model
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from keras.layers import Lambda
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from keras import backend as K
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import os
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import random
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from PIL import Image
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input1 = input('请输入图片名称1：')
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input2 = input('请输入图片名称2：')
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output = Lambda(lambda x: K.abs(x[0] - x[1]))
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weight = "./best.h5"
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# 加载模型
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# model = load_model(weight, custom_objects={'contrastive_loss': contrastive_loss, 'binary_accuracy': binary_accuracy})
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model = load_model(weight, custom_objects={'output': output})
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resize = 52
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img1 = cv2.imread(input1)
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img2 = cv2.imread(input2)
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img1 = cv2.resize(img1, (resize, resize)) / 255
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img2 = cv2.resize(img2, (resize, resize)) / 255
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img1 = np.expand_dims(img1, axis=0)
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img2 = np.expand_dims(img2, axis=0)
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result = model.predict([img1, img2])
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print(result)
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