Update app.py

app.py

@@ -100,10 +100,13 @@ def predict_image(img, confidence_threshold):
         # Check if either class meets the confidence threshold
         if result_2['AI Image'] >= confidence_threshold:
             label_2 = f"AI, Confidence: {result_2['AI Image']:.4f}"
+            result_2output += ['AI']
         elif result_2['Real Image'] >= confidence_threshold:
             label_2 = f"Real, Confidence: {result_2['Real Image']:.4f}"
+            result_2output += ['REAL']
         else:
             label_2 = "Uncertain Classification"
+            result_2output += ['UNCERTAIN']
     except Exception as e:
         label_2 = f"Error: {str(e)}"
     
@@ -127,10 +130,13 @@ def predict_image(img, confidence_threshold):
         # Check if either class meets the confidence threshold
         if result_3['AI'] >= confidence_threshold:
             label_3 = f"AI, Confidence: {result_3['AI']:.4f}"
+            result_3output += ['AI']
         elif result_3['Real'] >= confidence_threshold:
             label_3 = f"Real, Confidence: {result_3['Real']:.4f}"
+            result_3output += ['REAL']
         else:
             label_3 = "Uncertain Classification"
+            result_3output += ['UNCERTAIN']
     except Exception as e:
         label_3 = f"Error: {str(e)}"
     
@@ -154,17 +160,20 @@ def predict_image(img, confidence_threshold):
         # Check if either class meets the confidence threshold
         if result_4['AI'] >= confidence_threshold:
             label_4 = f"AI, Confidence: {result_4['AI']:.4f}"
+            result_4output += ['AI']
         elif result_4['Real'] >= confidence_threshold:
             label_4 = f"Real, Confidence: {result_4['Real']:.4f}"
+            result_4output += ['REAL']
         else:
             label_4 = "Uncertain Classification"
+            result_4output += ['UNCERTAIN']
     except Exception as e:
         label_4 = f"Error: {str(e)}"
     
     try:
         img_bytes = convert_pil_to_bytes(img_pil)
 
-        print(img_pill)
+        print(img)
         print(img_bytes)
         
         response5_raw = call_inference(img_bytes)