22 lines
531 B
Python
22 lines
531 B
Python
import tensorflow.keras as keras
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from PIL import Image
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import numpy as np
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import pdb
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def getI(path):
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return np.asarray(Image.open(path).convert('RGB').resize((100, 100))) / 255
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def predict(image1, image2):
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return model.predict([np.array([image2]), np.array([image1])])
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model = keras.models.load_model('./siamese_checkpoint')
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image1 = getI('data/fruits/fruits-360/Training/Avocado/r_254_100.jpg')
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image2 = getI('data/fruits/fruits-360/Training/Avocado/r_250_100.jpg')
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print(predict(image1, image2))
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pdb.set_trace()
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