Update app.py

app.py

@@ -11,45 +11,65 @@ fs = project.get_feature_store()
 
 
 mr = project.get_model_registry()
-model = mr.get_model("titanic_modal", version=3)
+model = mr.get_model("titanic_survival_modal", version=1)
 model_dir = model.download()
-model = joblib.load(model_dir + "/titanic_model.pkl")
+model = joblib.load(model_dir + "/titanic_survival_model.pkl")
 
-def titanic(pclass, sex, sibsp, parch):
-    input_list = []
-    
-    input_list.append(int(sex)) # value returned by dropdown is index of option selected
-    input_list.append(int(pclass+1)) # index starts at 0 so increment by 1
-    input_list.append(int(sibsp))
-    input_list.append(int(parch))
-
-    print(input_list)
-    # 'res' is a list of predictions returned as the label.
-    #res = model.predict(np.asarray(input_list).reshape(1, -1), ntree_limit=model.best_ntree_limit)  # for xgboost
-    print(np.asarray(input_list).reshape(1, -1))
-    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.
-    print(res[0]) # 0/1 
-    # below is just for testing
+def titanic(pclass, sex, age, fare, embarked, title, isalone):
+    input_list = [] 
+    input_list.append(int(pclass+1))
+    input_list.append(int(sex)) 
+    if age<=16:
+      input_list.append(0)
+    elif age>16 and age<=32:
+      input_list.append(1)
+    elif age>32 and age<=48:
+      input_list.append(2)
+    elif age>48 and age<=64:
+      input_list.append(3)
+    else:
+      input_list.append(4)
+    if fare<=7.91:
+      input_list.append(0)
+    elif fare>7.91 and fare<=14.454:
+      input_list.append(1)
+    elif fare>14.454 and fare<=31:
+      input_list.append(2)
+    else:
+      input_list.append(3)
+    if embarked=='C':
+      input_list.append(1)
+    elif embarked=='S':
+      input_list.append(0) 
+    else:
+      input_list.append(2) 
+    input_list.append(title)
+    input_list.append(isalone)
+    res = model.predict(np.asarray(input_list,dtype=object).reshape(1,-1))
     if res[0] == 0: #ded
-        passenger_url = "https://media.istockphoto.com/id/157612035/sv/foto/shipwreck.jpg?s=612x612&w=0&k=20&c=BSVml8_SqgvSmEijAprhniyp_Wa_l5qIIVIxhmmBgBQ="
+      person="dead"
+      passenger_url = "https://raw.githubusercontent.com/irena123333/titanic-prediction/main/dead.png"
+      
     else:
-        passenger_url = "https://i.chzbgr.com/full/5420028160/hD88BD9FE/like-a-boss"
+      person="survived"
+      passenger_url = "https://raw.githubusercontent.com/irena123333/titanic-prediction/main/survived.png"
     img = Image.open(requests.get(passenger_url, stream=True).raw)            
     return img
-        
+      
 demo = gr.Interface(
     fn=titanic,
     title="Titanic Passenger Survival Predictive Analytics",
     description="If one person is on titanic, predict whether he or she will survive.",
     allow_flagging="never",
-    inputs=[
+    inputs=[gr.inputs.Dropdown(choices=["Class 1","Class 2","Class 3"], type="index", label="pclass"),
         gr.inputs.Dropdown(choices=["Male", "Female"], type="index", label="sex"),
-        gr.inputs.Dropdown(choices=["Class 1","Class 2","Class 3"], type="index", label="pclass"),
-        gr.inputs.Number(default=1.0, label="SibSp"),
-        gr.inputs.Number(default=1.0, label="parch"),
+        gr.inputs.Slider(0,150,label='Age'),
+        gr.inputs.Number(default=8.0, label="Fare"),
+        gr.inputs.Radio(default='S', label="Embarkation Port", choices=['C', 'Q', 'S']),
+        gr.inputs.Dropdown(choices=["Master","Miss","Mr","Mrs","Other"], type="index", label="Title"),
+        gr.inputs.Dropdown(choices=["False", "True"], type="index", label="IsAlone"),
         ],
+        
     outputs=gr.Image(type="pil"))
 
 demo.launch()