Update thresholds

app.py

@@ -142,14 +142,14 @@ def predict_fn(input_img):
     hair_result_probabilty = float(hair_probabilities[0][1].round(3))
     old_result_probabilty = float(old_lr_probabilities[0][1].round(3))
     # get decision string
-    if result_probabilty > 0.77:
+    if result_probabilty > 0.85:
         if hair_result_probabilty < 0.24:
             logger.info("hair_result_probabilty < 0.5")
             result_probabilty = hair_result_probabilty
             decision = "AUTO REJECT"
         else:
             decision = "AUTO ACCEPT"
-    elif result_probabilty < 0.2:
+    elif result_probabilty < 0.24:
         logger.info("result_probabilty < 0.2")
         decision = "AUTO REJECT"
     elif old_result_probabilty < 0.06:
@@ -172,8 +172,8 @@ iface = gr.Interface(
     outputs="text",
     description="""
     The model returns the probability of the image being a base body. If
-    probability > 0.77, the image can be automatically tagged as a base body. If
-    probability < 0.24, the image can be automatically REJECTED as NOT as base
+    probability > 0.85, the image can be automatically tagged as a base body. If
+    probability < 0.25, the image can be automatically REJECTED as NOT as base
     body. All other cases will be submitted for moderation.
 
     Please flag if you think the decision is wrong.