2022-06-02 01:56:52 +02:00
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import numpy as np
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import tensorflow as tf
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def image_clasification(image_path, model):
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# loaded_model = keras.models.load_model("my_model")
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class_names = ['door', 'refrigerator', 'shelf']
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img = tf.keras.utils.load_img(
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image_path, target_size=(180, 180)
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)
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img_array = tf.keras.utils.img_to_array(img)
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img_array = tf.expand_dims(img_array, 0) # Create a batch
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predictions = model.predict(img_array)
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score = tf.nn.softmax(predictions[0])
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# print(
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# "This image most likely belongs to {} with a {:.2f} percent confidence."
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# .format(class_names[np.argmax(score)], 100 * np.max(score))
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# )
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return class_names[np.argmax(score)]
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