Update app.py

app.py

@@ -225,32 +225,28 @@ 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 != '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)
+    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)
 
     elif model_name == 'Efficientnet Art':
         print('Effnet Art is running')
         predictions = pre_process_img_effNetArt(user_image)
-        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(predictions)
+
+        
+    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)
 
     print(model_name)
     print(predictions[0])