tested prediction

requirements.txt

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

test.py

@@ -0,0 +1,33 @@
+import io
+import numpy as np
+import tensorflow as tf
+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)
+
+print(f"Benign Prediction: {benign_prediction}")
+print(f"Malignant Prediction: {malignant_prediction}")