Update app.py

app.py

@@ -40,7 +40,8 @@ def load_model(model_repo_id):
 def predict(pilimg,Threshold):
 
     image_np = pil_image_as_numpy_array(pilimg)
-    return predict2(image_np,float(Threshold)),predict3(image_np,float(Threshold))
+    Thresholdf=float(Threshold)
+    return predict2(image_np,Thresholdf),predict3(image_np,Thresholdf)
 
 def predict2(image_np,Threshold):
 
@@ -168,8 +169,8 @@ 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=0.99, value=0.6 ,label="Threshold",info="[not in used]to set prediction confidence threshold")],
-    outputs=[gr.Image(type="pil",label="Base Model"),gr.Image(type="pil",label="Tuned Model")],
+    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")],
+    outputs=[gr.Image(type="pil",label="Base Model Inference"),gr.Image(type="pil",label="Tuned Model Inference")],
     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=[[test1],[test2],[test3],[test4],[test5],[test6],[test7],[test8],[test9],[test10],[test11],[test12],],
@@ -207,8 +208,8 @@ base_image = gr.Interface(
 
 video = gr.Interface(
     fn=lambda x,y: [x,y], #video_demo,
-    inputs=[gr.Video(label="base model Video"),gr.Video(label="tuned model Video")], 
-    outputs=[gr.Video(label="Base model inferenced video"), gr.Video(label="Tuned model inferenced video")],
+    inputs=[gr.Video(label="Base Model Video",interactive=False),gr.Video(label="Tuned Model Video",interactive=False)], 
+    outputs=[gr.Video(label="Base Model Inferenced Video"), gr.Video(label="Tuned Model Inferenced Video")],
     examples=[
         [a, b]
     ],