Update example.py

example.py

@@ -1,22 +1,19 @@
-
-from shepards_gift_tool import BrainTumorClassifier
-
-# 1. Create an instance of the classifier.
-print("Initializing Shepard's Gift classifier...")
-classifier = BrainTumorClassifier()
-print("Classifier ready.")
-
-# 2. Define the path to the image the user wants to analyze.
-image_to_test = "path/to/your/mri_scan.jpg" 
-
-# 3. Get the prediction.
-print(f"\nAnalyzing image: {image_to_test}")
-result = classifier.predict(image_to_test)
-
-# 4. Print the clean, simple result.
-print("\n--- 🏆 Analysis Complete ---")
-if "error" in result:
-    print(f"An error occurred: {result['error']}")
-else:
-    print(f"Predicted Class: {result['predicted_class']}")
-    print(f"Confidence:      {result['confidence']}")
+import os
+os.environ["KERAS_BACKEND"] = "tensorflow"
+
+import keras
+from huggingface_hub import hf_hub_download
+from PIL import Image
+import numpy as np
+
+# 1. Download the model file
+print("--- Downloading model... ---")
+model_path = hf_hub_download(
+    repo_id="VeduCo/D-Shepard-p1-57",
+    filename="ShepardsGift_final_model.keras" # Important: Use the correct filename
+)
+
+# 2. Load the model
+model = keras.saving.load_model(model_path)
+print("--- Model loaded successfully! ---")
+model.summary()