Set threshold 0.4, multilabel textbox hidden

app.py

@@ -144,6 +144,9 @@ def get_img_array(img_path):
 
 
 def get_prediction(img_path):
+    # adjust threshold for accuracy
+    threshold = 0.4
+    
     # check the image path
     print(f"Image path: {img_path}")
     # also display the original filename for info
@@ -156,7 +159,7 @@ def get_prediction(img_path):
     # binary label
     pred_binary = keras_binary_model(img_array, training=False)
     print(f"Keras binary label: {pred_binary}")
-    if pred_binary[0][0] > 0.5:
+        if pred_binary[0][0] > threshold:
         fake = "Fake"
     else:
         fake = "Real"
@@ -165,7 +168,7 @@ def get_prediction(img_path):
     pred_multi = keras_multi_model(img_array, training=False)
     print(f"Keras multi label: {pred_multi}")
     # Cut at the sigmoid 0.5 threshold
-    fake_parts = np.where(pred_multi > 0.5, 1, 0)
+    fake_parts = np.where(pred_multi > threshold, 1, 0)
     print(f"Multi label: {fake_parts}")
     # Format each of the fake face parts
     parts_message = dict()
@@ -255,7 +258,8 @@ with gr.Blocks() as demo:
                 interactive=False, lines=2)
             text_3 = gr.Text(
                 label="Multi label, Efficient net v2 B0",
-                interactive=False, lines=7)
+                interactive=False, lines=7, 
+                visible=False)
             """
             text_3 = gr.Text(label="Sashi's model",
                              interactive=False, lines=3)