adsf

app.py

@@ -47,7 +47,26 @@ model = mr.get_model("titanic_modal", version=3)
 model_dir = model.download()
 model = joblib.load(model_dir + "/titanic_model.pkl")
 
-df = pd
+
+catToInput = {
+    "Sex": ["male", "female"],
+    "Embarked": ["Southampton", "Cherbourg", "Queenstown"],
+    "Pclass": ["First", "Second", "Thrid"]
+}
+
+cityToInput = {
+    "Southampton": "S",
+    "Cherbourg": "C",
+    "Queenstown": "Q"
+}
+
+classToInput = {
+    "First": 1,
+    "Second": 2,
+    "Third": 3
+}
+
+
 # features = pd.read_csv(
 #     "https://raw.githubusercontent.com/Nathanotal/remoteFiles/main/titanicCleaned.csv")
 # features = features.drop(columns=["survived"])
@@ -65,7 +84,8 @@ columnHeaders = ["Pclass", "Sex", "Age", "SibSp",
 
 
 def titanic(Pclass, Sex, Age, SibSp, Parch, Fare, Embarked):
-
+    Embarked = cityToInput[Embarked]
+    Pclass = classToInput[Pclass]
     # Create a dataframe from the input values
     input_variables = pd.DataFrame(
         [[Pclass, Sex, Age, SibSp, Parch, Fare, Embarked, 1.0]], columns=columnHeaders)
@@ -109,25 +129,35 @@ def titanic(Pclass, Sex, Age, SibSp, Parch, Fare, Embarked):
     return img, img2
 
 
-catToInput = {
-    "Sex": ["male", "female"],
-    "Embarked": ["S", "C", "Q"],
-    "Pclass": [0, 1, 2]
-}
-
-
 featureLabels = ["Pclass", "Name", "Sex", "Age", "SibSp",
                  "Parch", "Ticket", "Fare", "Cabin", "Embarked"]
-
 for feature in featureLabels:
     if feature in numericalInputs:
-        inputs.append(gr.inputs.Number(default=1.0, label=feature))
+        if feature == 'Age':
+            inputs.append(gr.inputs.Number(9, 75, 1, label='Age (years)'))
+        if feature == 'SibSp':
+            inputs.append(gr.inputs.Number(
+                0, 10, 1, label='Number of siblings/spouses aboard'))
+        if feature == 'Parch':
+            inputs.append(gr.inputs.Number(
+                0, 10, 1, label='Number of parents/children aboard'))
+        if feature == 'Fare':
+            inputs.append(gr.inputs.Number(0, 1000, 1, label='Ticket fare'))
+        else:
+            raise Exception(f'Feature: "{feature}" not found')
     elif feature in worthlessInputs:
         pass
         # inputs.append(gr.Inputs.Textbox(default='text', label=feature))
     elif feature in categoricalInputs:
-        inputs.append(gr.inputs.Dropdown(
-            choices=catToInput.get(feature), default="a", label=feature))
+        if feature == "Sex":
+            inputs.append(gr.inputs.Dropdown(
+                choices=catToInput.get(feature), default="male", label=feature))
+        if feature == "Embarked":
+            inputs.append(gr.inputs.Dropdown(
+                choices=catToInput.get(feature), default="Southampton", label='City of embarkation'))
+        if feature == "Pclass":
+            inputs.append(gr.inputs.Dropdown(
+                choices=catToInput.get(feature), default=3, label='Ticket class'))
     else:
         raise Exception(f'Feature: "{feature}" not found')