refactor: rename predict_image_with_json to predict_with_ensemble and update its implementation to return consensus label

app_mcp.py

@@ -265,9 +265,9 @@ def get_consensus_label(results):
     color = {"AI": "red", "REAL": "green", "UNCERTAIN": "orange"}.get(consensus, "gray")
     return f"<b><span style='color:{color}'>{consensus}</span></b>"
 
-# Update predict_image_with_json to return consensus label
+# Update predict_with_ensemble to return consensus label
 
-def predict_image_with_json(img, confidence_threshold, augment_methods, rotate_degrees, noise_level, sharpen_strength):
+def predict_with_ensemble(img, confidence_threshold, augment_methods, rotate_degrees, noise_level, sharpen_strength):
     # Ensure img is a PIL Image (if it's not already)
     if not isinstance(img, Image.Image):
         try:
@@ -362,7 +362,7 @@ def predict_image_with_json(img, confidence_threshold, augment_methods, rotate_d
     # 6. Perform forensic processing
     gradient_image = gradient_processing(img_np_og)  # Added gradient processing
     minmax_image = minmax_process(img_np_og)  # Added MinMax processing
-    bitplane_image = bit_plane_extractor(img_np_og)
+    bitplane_image = bit_plane_extractor(img_pil)
     
 
     # First pass - standard analysis