Update app.py

app.py

@@ -60,7 +60,7 @@ def predict2(image_np):
         category_index,
         use_normalized_coordinates=True,
         max_boxes_to_draw=20,
-        min_score_thresh=0.3,
+        min_score_thresh=0.38,
         agnostic_mode=False,
         line_thickness=2)
 
@@ -91,7 +91,7 @@ def predict4(image_np):
         category_index,
         use_normalized_coordinates=True,
         max_boxes_to_draw=20,
-        min_score_thresh=.30,
+        min_score_thresh=.38,
         agnostic_mode=False,
         line_thickness=2)
 
@@ -175,7 +175,7 @@ base_image = gr.Interface(
     inputs=[gr.Image(type="pil"),gr.Slider(minimum=0.01, maximum=0.99, value=0.6 ,label="Threshold(WIP)",info="[not in used]to set prediction confidence threshold")],
     outputs=gr.Image(type="pil"),
     title="Luffy and Chopper face detection (Base mobile net model)",
-    description="Upload a Image for prediction or click on below examples",
+    description="Upload a Image for prediction or click on below examples. Prediction confident >38%",
     examples=[[test1],[test2],[test3],[test4],[test5],[test6],[test7],[test8],[test9],[test10],[test11],[test12],],
     cache_examples=True
     )#.launch(share=True)
@@ -185,7 +185,7 @@ tuned_image = gr.Interface(
     inputs=gr.Image(type="pil"),
     outputs=gr.Image(type="pil"),
     title="Luffy and Chopper face detection (tuned mobile net model)",
-    description="Upload a Image for prediction or click on below examples. Mobile net tuned with data Augmentation",
+    description="Upload a Image for prediction or click on below examples. Mobile net tuned with data Augmentation. Prediction confident >38%",
     examples=[[test1],[test2],[test3],[test4],[test5],[test6],[test7],[test8],[test9],[test10],[test11],[test12],],
     cache_examples=True
     )#.launch(share=True)