Update app.py

app.py

@@ -27,7 +27,7 @@ def predict_fn(input_img):
     with torch.no_grad():
         image_features = clip_model.encode_image(image).numpy()
         input_df = pd.DataFrame(image_features[0].reshape(1, -1))
-        quality_score = predictor.predict(input_df).iloc[0]
+        quality_score = float(predictor.predict(input_df).iloc[0])
 
     logger.info(f"decision: {quality_score}")
     decision_json = json.dumps({"quality_score": quality_score}).encode("utf-8")
@@ -40,18 +40,8 @@ iface = gr.Interface(
     inputs="image",
     outputs="text",
     description="""
-    The model returns the probability of the image being a base body. If
-    probability > 0.9, the image can be automatically tagged as a base body. If
-    probability < 0.2, 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.
+    The model returns quality score for an avatar based on visual apeal and humanoid appearance.
     """,
     allow_flagging="manual",
-    flagging_options=[
-        ": decision should be accept",
-        ": decision should be reject",
-        ": decision should be moderation",
-    ],
 )
 iface.launch()