Update app.py

app.py

@@ -280,8 +280,13 @@ def predict(image):
     print("Min value of image:", np.min(annotated_img))
     print("Max value of image:", np.max(annotated_img))
 
-    # Normalize output image (again)
-    annotated_img = (annotated_img / 255.0 - mean)/std
+    # # Normalize output image using ImageNet-style normalization (again)
+    # annotated_img = (annotated_img / 255.0 - mean)/std
+
+    # Normalize output image using Min-Max normalization
+    min_val = np.min(annotated_img)
+    max_val = np.max(annotated_img)
+    annotated_img = (annotated_img - min_val) / (max_val - min_val)
 
     print("Min value of image after normalization:", np.min(annotated_img))
     print("Max value of image after normalization:", np.max(annotated_img))