Update app.py

app.py

@@ -43,9 +43,9 @@ def predict(pilimg,Threshold):
     if type(Threshold) is None:
         Threshold=0.38
         
-    return predict2(image_np),predict3(image_np),Threshold
+    return predict2(image_np,Threshold),predict3(image_np,Threshold),Threshold
 
-def predict2(image_np):
+def predict2(image_np,Threshold):
 
     results = detection_model(image_np)
 
@@ -63,7 +63,7 @@ def predict2(image_np):
         category_index,
         use_normalized_coordinates=True,
         max_boxes_to_draw=20,
-        min_score_thresh=0.38,
+        min_score_thresh=Threshold,#0.38,
         agnostic_mode=False,
         line_thickness=2)
 
@@ -72,7 +72,7 @@ def predict2(image_np):
     return result_pil_img2
 
 
-def predict3(image_np):
+def predict3(image_np,Threshold):
 
     results = detection_model2(image_np)
 
@@ -90,7 +90,7 @@ def predict3(image_np):
         category_index,
         use_normalized_coordinates=True,
         max_boxes_to_draw=20,
-        min_score_thresh=.38,
+        min_score_thresh=Threshold,#.38,
         agnostic_mode=False,
         line_thickness=2)
 
@@ -172,13 +172,13 @@ 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 Threshold",info="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")],
 
     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",
     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=
-        [[test1,0.38],[test2,0.38],[test3,0.38],[test4,0.38],[test5,0.38],[test6,0.38],[test7,0.38],[test8,0.38],[test9,0.38],[test10,0.38],[test11,0.38],[test12,0.38],],
+        [[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"
     )