Update app.py

app.py

@@ -42,7 +42,7 @@ def predict(pilimg,Threshold):
     image_np = pil_image_as_numpy_array(pilimg)
     
     if Threshold is None or Threshold == 0:
-        Threshold=0.88
+        Threshold=threshold_d
     else:
         Threshold= float(Threshold)
         
@@ -52,8 +52,8 @@ def predict2(image_np,Threshold):
 
     results = detection_model(image_np)
     
-    if Threshold is None or Threshold == 0:
-        Threshold=threshold_d
+    # if Threshold is None or Threshold == 0:
+    #     Threshold=threshold_d
         
     # different object detection models have additional results
     result = {key:value.numpy() for key,value in results.items()}
@@ -179,11 +179,11 @@ 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=threshold_d ,label="[WIP]To change default 0.38 prediction confidence Threshold",info="[not in used]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. Range 0.01 to 1",info="Select any image below to start, you may amend threshold after first inference")],
 
-    outputs=[gr.Image(type="pil",label="Base Model Inference"),gr.Image(type="pil",label="Tuned Model Inference"),gr.Textbox(label="[WIP]Both images inferenced threshold")],
+    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",
+    description="Upload a Image for prediction or click on below examples. Prediction confident is defaut t >38%, you may adjust after first inference",
     examples=
         [[test1],[test2],[test3],[test4],[test5],[test6],[test7],[test8],[test9],[test10],[test11],[test12],],
     cache_examples=True,examples_per_page=12 #,label="select image with 0.38 threshold to inference, you may amend threshold after inference"