22 lines
494 B
Python
22 lines
494 B
Python
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from tensorflow import keras
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from DataGenerator import DataGenerator
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number_of_classes: int = 10
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size_of_batch_test: int = 100
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model_id: int = 49
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test_data = DataGenerator(
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train=False,
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size_of_batch=size_of_batch_test,
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number_of_classes=number_of_classes,
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do_shuffle=False,
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)
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keras.backend.clear_session()
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network = keras.models.load_model("./Model_" + str(model_id) + ".h5")
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test_loss, test_acc = network.evaluate(x=test_data)
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print(f"Correct: {test_acc * 100.0:.2f}%")
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