37 lines
1009 B
Python
37 lines
1009 B
Python
import io
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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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from PIL import Image
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def preprocess_image_bytes(image):
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image = Image.open(io.BytesIO(image))
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image = np.array(image)
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image = np.expand_dims(image, axis=0)
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return image
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# Import Image and Model as bytes (Simulate call from API)
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benign_image_bytes = open("data/test/benign/5.jpg", "rb").read()
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malignant_image_bytes = open("data/test/malignant/1.jpg", "rb").read()
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model_bytes = open("models/mobilenet_v3.keras", "rb")
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# Convert model to Keras model
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model_file = open("model.keras", "wb").write(model_bytes.read())
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model = tf.keras.models.load_model("model.keras")
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os.remove("model.keras")
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benign_image = preprocess_image_bytes(benign_image_bytes)
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malignant_image = preprocess_image_bytes(malignant_image_bytes)
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benign_prediction = model.predict(benign_image)
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malignant_prediction = model.predict(malignant_image)
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print(f"Benign Prediction: {benign_prediction}")
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print(f"Malignant Prediction: {malignant_prediction}")
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