43 lines
1.7 KiB
Python
43 lines
1.7 KiB
Python
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import numpy as np
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import tensorflow as tf
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import os
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#Import Data
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PATH = os.path.join(os.getcwd(), "crop-data")
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validation_data = os.path.join(PATH, "valid")
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validation_data_32 = tf.keras.utils.image_dataset_from_directory(validation_data,
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shuffle=True,
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batch_size=32,
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image_size=(160,160))
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validation_data_64 = tf.keras.utils.image_dataset_from_directory(validation_data,
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shuffle=True,
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batch_size=64,
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image_size=(160,160))
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AUTOTUNE = tf.data.AUTOTUNE
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validation_data_32 = validation_data_32.prefetch(buffer_size=AUTOTUNE)
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validation_data_64 = validation_data_64.prefetch(buffer_size=AUTOTUNE)
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validation_data_32 = validation_data_32.map(lambda x,y: (x, tf.one_hot(y,38)))
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validation_data_64 = validation_data_64.map(lambda x,y: (x, tf.one_hot(y,38)))
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model1 = tf.keras.models.load_model("crop-classifier.keras")
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model2 = tf.keras.models.load_model("crop-classifier-64-batch.keras")
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model3 = tf.keras.models.load_model("crop-classifier-callbacks.keras")
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result = model1.evaluate(validation_data_32)
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print(f"Validation Loss: {result[0]}")
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print(f"Accuracy: {result[1]}")
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result = model2.evaluate(validation_data_64)
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print(f"Validation Loss: {result[0]}")
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print(f"Accuracy: {result[1]}")
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result = model3.evaluate(validation_data_64)
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print(f"Validation Loss: {result[0]}")
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print(f"Accuracy: {result[1]}")
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