Update app.py

app.py

@@ -16,39 +16,5 @@ model_dir = model.download()
 model = joblib.load(model_dir + "/titanic_model.pkl")
 
 
-def passenger(pclass, sex, family, groupedage):
-    input_list = []
-    input_list.append(pclass)
-    input_list.append(sex)
-    input_list.append(family)
-    input_list.append(groupedage)
-    # 'res' is a list of predictions returned as the label.
-    res = model.predict(np.asarray(input_list).reshape(1, -1)) 
-    # We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want 
-    # the first element.
-    if res[0] == 1:
-        passenger_url =  "https://cdn.pixabay.com/photo/2018/08/02/18/58/survival-3580200_960_720.png"
-    else:
-        passenger_url = "https://pngimg.com/uploads/death/death_PNG55.png"
-    
-    img = Image.open(requests.get(passenger_url, stream=True).raw)
-    return img
-#return res[0]         
-
-
-demo_titanic = gr.Interface(
-    fn=passenger,
-    title="Titanic Predictive Analytics",
-    description="Experiment to predict if a passenger survived or died in the titanic",
-    allow_flagging="never",
-    inputs=[
-        gr.inputs.Number(default=1.0, label="Pclass (Min:1, Max=3"),
-        gr.inputs.Number(default=1.0, label="Sex (Female:0 and Male:1)"),
-        gr.inputs.Number(default=1.0, label="Family (Number of family members in the boat[0,7])"),
-        gr.inputs.Number(default=1.0, label="Age (Child:0, Adult:1 and Old:2)")
-        ], 
-    outputs=gr.Image(type="pil"))
-
-#outputs=gr.Label(num_top_classes=2)
-demo_titanic.launch()
+