26 lines
635 B
Python
26 lines
635 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 ipdb
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class g:
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def __init__(self, path):
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self.image = np.asarray(Image.open(path).convert('RGB').resize((100, 100))) / 255
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def show(self):
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self.image.show()
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def predict(image1, image2):
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return model.predict([np.array([image2.image]), np.array([image1.image])])
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model = keras.models.load_model('../siamese_100x100_pretrainedb_vgg16')
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image1 = g('data/fruits/fruits-360/Training/Avocado/r_254_100.jpg')
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image2 = g('data/fruits/fruits-360/Training/Avocado/r_250_100.jpg')
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print(predict(image1, image2))
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ipdb.set_trace()
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