Update app.py

app.py

@@ -48,7 +48,10 @@ def predict(pilimg,Threshold):
 def predict2(image_np,Threshold):
 
     results = detection_model(image_np)
-
+    
+    if type(Threshold) is None:
+        Threshold=threshold_d
+        
     # different object detection models have additional results
     result = {key:value.numpy() for key,value in results.items()}
     
@@ -73,7 +76,10 @@ def predict2(image_np,Threshold):
 
 
 def predict3(image_np,Threshold):
-
+    
+    if type(Threshold) is None:
+        Threshold=threshold_d
+        
     results = detection_model2(image_np)
 
     # different object detection models have additional results
@@ -175,7 +181,7 @@ base_image = gr.Interface(
 #    inputs=[gr.Image(type="pil"),gr.Slider(minimum=0.01, maximum=1, value=0.38 ,label="Threshold",info="[not in used]to set prediction confidence threshold")],
     inputs=[gr.Image(type="pil"),gr.Textbox(value=threshold_d ,label="To change default 0.38 prediction confidence Threshold",info="Select image with 0.38 threshold to start, you may amend threshold after each first image inference")],
 
-    outputs=[gr.Image(type="pil",label="Base Model Inference"),gr.Image(type="pil",label="Tuned Model Inference"),gr.Textbox(label="Tuned Model Inference")],
+    outputs=[gr.Image(type="pil",label="Base Model Inference"),gr.Image(type="pil",label="Tuned Model Inference"),gr.Textbox(label="Both images inferenced threshold")],
     title="Luffy and Chopper Head detection. SSD mobile net V2 320x320",
     description="Upload a Image for prediction or click on below examples. Prediction confident >38% will be shown in dectected images. Threshold slider is WIP",
     examples=