Update app.py

app.py

@@ -41,7 +41,7 @@ def predict(pilimg,Threshold):
 
     image_np = pil_image_as_numpy_array(pilimg)
     if type(Threshold) is None:
-        Threshold=0.38
+        Threshold=threshold_d
         
     return predict2(image_np,Threshold),predict3(image_np,Threshold),Threshold
 
@@ -144,6 +144,7 @@ b = os.path.join(os.path.dirname(__file__), "data/c_tuned_detected.mp4")  # Vide
 #     return [video1, video2]
 
 label_id_offset = 0    
+threshold_d=0.38
 REPO_ID = "apailang/mytfodmodel"
 detection_model = load_model(REPO_ID)
 REPO_ID2 = "apailang/mytfodmodeltuned"
@@ -172,7 +173,7 @@ test12 = os.path.join(os.path.dirname(__file__), "data/test12.jpeg")
 base_image = gr.Interface(
     fn=predict,
 #    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=0.38 ,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")],
+    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")],
     title="Luffy and Chopper Head detection. SSD mobile net V2 320x320",