Update app.py

app.py

@@ -225,25 +225,32 @@ with main_col_two:
 if user_image is not None and model_name is not None:
     predictions = []
     # preprocess image and run the user selected model
-    if model_name == 'CNN':
-        print('CNN is running')
-        predictions = pre_process_img(user_image)
-    elif model_name == 'Efficientnet':
-        print('Effnet is running')
-        predictions = pre_process_img_effNet(user_image)
+    if model_name != 'Efficientnet Art':
+        if model_name == 'CNN':
+            print('CNN is running')
+            predictions = pre_process_img(user_image)
+        elif model_name == 'Efficientnet':
+            print('Effnet is running')
+            predictions = pre_process_img_effNet(user_image)
+        if predictions[0] < 0.5:
+             result_word = "AI Generated"
+        else:
+             result_word = "REAL"
+        if user_image is not None:
+            if len(predictions) > 0: 
+                result_placeholder.markdown(f"<div class='result'> <span class = 'prediction'>Prediction: {predictions[0][0]:.2%}</span> <br> It is a <span class = resultword> {result_word} </span> image. </div>", unsafe_allow_html=True)
+
     elif model_name == 'Efficientnet Art':
         print('Effnet Art is running')
         predictions = pre_process_img_effNetArt(user_image)
-
-    if predictions[0] < 0.5:
-         result_word = "AI Generated"
-    else:
-         result_word = "REAL"
-
-    # display the result and the prediction
-    if user_image is not None:
-        if len(predictions) > 0: 
-            result_placeholder.markdown(f"<div class='result'> <span class = 'prediction'>Prediction: {predictions[0][0]:.2%}</span> <br> It is a <span class = resultword> {result_word} </span> image. </div>", unsafe_allow_html=True)
+        scaled_prediction = min(predictions[0] * 10000, 1)
+        if scaled_prediction < 0.5:
+             result_word = "AI Generated"
+        else:
+             result_word = "REAL"
+        if user_image is not None:
+            if len(predictions) > 0: 
+                result_placeholder.markdown(f"<div class='result'> <span class = 'prediction'>Prediction: {scaled_prediction:.2%}</span> <br> It is a <span class = resultword> {result_word} </span> image. </div>", unsafe_allow_html=True)
 
     print(model_name)
     print(predictions[0])