fix: normalization of viz

app.py

@@ -78,8 +78,19 @@ def interface(classifier):
         mask = results["segmentation_mask"]
         print(mask)
 
+        # Normalize the mask to 0-1 range based on its min/max values
+        if mask.max() > mask.min(): # Avoid division by zero if mask is perfectly flat
+            normalized_mask = (mask - mask.min()) / (mask.max() - mask.min())
+        else:
+            normalized_mask = np.zeros_like(mask) # If flat, just make it all black
+
+        # Use the normalized mask for visualization
+        mask_viz = (normalized_mask * 255).astype(np.uint8)
+
+
+        binary_for_overlay = normalized_mask > 0.5
         overlay = image_np.copy()
-        overlay[mask < 0.2] = overlay[mask < 0.2] * 0
+        overlay[~binary_for_overlay] = (overlay[~binary_for_overlay] * 0.3).astype(np.uint8)
 
         output_str = f"Predicted Class: {results['predicted_class']}\n"
         output_str += f"Confidence: {results['confidence']*100:.2f}%\n\n"