requirements.txt

@@ -1,2 +1,2 @@
-pillow==10.3.0
+pillow
-tensorflow==2.16.1
+tensorflow

test.py

@@ -1,36 +0,0 @@
-import io
-import numpy as np
-import tensorflow as tf
-import os
-from PIL import Image
-
-
-def preprocess_image_bytes(image):
-    image = Image.open(io.BytesIO(image))
-    image = np.array(image)
-    image = np.expand_dims(image, axis=0)
-
-    return image
-
-
-# Import Image and Model as bytes (Simulate call from API)
-benign_image_bytes = open("data/test/benign/5.jpg", "rb").read()
-malignant_image_bytes = open("data/test/malignant/1.jpg", "rb").read()
-model_bytes = open("models/mobilenet_v3.keras", "rb")
-
-
-# Convert model to Keras model
-model_file = open("model.keras", "wb").write(model_bytes.read())
-model = tf.keras.models.load_model("model.keras")
-
-
-benign_image = preprocess_image_bytes(benign_image_bytes)
-malignant_image = preprocess_image_bytes(malignant_image_bytes)
-
-benign_prediction = model.predict(benign_image)
-malignant_prediction = model.predict(malignant_image)
-
-os.remove("model.keras")
-
-print(f"Benign Prediction: {benign_prediction}")
-print(f"Malignant Prediction: {malignant_prediction}")