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Update app.py
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app.py
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@@ -8,17 +8,18 @@ import os
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import numpy as np
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labels= { '
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HEIGHT,WIDTH=224,224
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NUM_CLASSES=6
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model=load_model('best_model.h5')
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def classify_image(inp):
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inp = inp.reshape((-1, HEIGHT,WIDTH, 3))
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inp = tf.keras.applications.nasnet.preprocess_input(inp)
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prediction = model.predict(inp)
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label = dict((v,k) for k,v in labels.items())
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predicted_class_indices=np.argmax(prediction,axis=1)
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return {labels[i]: float(predicted_class_indices[i]) for i in range(NUM_CLASSES)}
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import numpy as np
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labels= {'Burger King': 0, 'KFC': 1,'McDonalds': 2,'Other': 3,'Starbucks': 4,'Subway': 5}
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HEIGHT,WIDTH=224,224
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NUM_CLASSES=6
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model=load_model('best_model.h5')
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def classify_image(inp):
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np.random.seed(143)
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inp = inp.reshape((-1, HEIGHT,WIDTH, 3))
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inp = tf.keras.applications.nasnet.preprocess_input(inp)
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prediction = model.predict(inp)
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#label = dict((v,k) for k,v in labels.items())
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predicted_class_indices=np.argmax(prediction,axis=1)
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return {labels[i]: float(predicted_class_indices[i]) for i in range(NUM_CLASSES)}
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