initial commit

app.py

@@ -0,0 +1,54 @@
+import gradio as gr
+import numpy as np
+from PIL import Image
+import requests
+
+import hopsworks
+import joblib
+
+project = hopsworks.login()
+fs = project.get_feature_store()
+
+
+mr = project.get_model_registry()
+model = mr.get_model("titanic_modal", version=1)
+model_dir = model.download()
+model = joblib.load(model_dir + "/titanic_model.pkl")
+
+
+def titanic(Sex_Code,Pclass,Embarked_Code,Title_Code,FamilySize,AgeBin_Code,FareBin_Code):
+    input_list = []
+    input_list.append(Sex_Code)
+    input_list.append(Pclass)
+    input_list.append(Embarked_Code)
+    input_list.append(Title_Code)
+    input_list.append(FamilySize)
+    input_list.append(AgeBin_Code)
+    input_list.append(FareBin_Code)
+    # '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.
+    flower_url = "https://images.pexels.com/photos/8384595/pexels-photo-8384595.jpeg?auto=compress&cs=tinysrgb&w=1260&h=750&dpr=1"
+    img = Image.open(requests.get(flower_url, stream=True).raw)            
+    return img
+        
+demo = gr.Interface(
+    fn=titanic,
+    title="Titanic Survivor Predictive Analytics",
+    description="Experiment with input parameters to predict survival",
+    allow_flagging="never",
+    inputs=[
+        #0= female 1=male
+        gr.Radio(["Female", "Male"], label="Gender", type="index"),
+        gr.Radio([1, 2, 3], label="Ticket class", type = "value"),
+        gr.Radio([1, 2, 3], label="Embarked from", type="index"),
+        gr.Radio(["Master", "Miscellenaous", "Miss", "Mr", "Mrs" ], label="Title"),
+        gr.Radio([1,2,3,4,5,6,7,8,11], label="Family size", type="value"),
+        gr.Radio(["age<=16", "16<age<=32", "32<age<=48", "48<age<=64", "64<age<=80"], label="Age", type="index"),
+        gr.Radio(["Low", "Medium", "High", "Very high"], label="Fare", type="index"),
+        ],
+    outputs=gr.Image(type="pil"))
+
+demo.launch()
+

requirements.txt

@@ -0,0 +1,3 @@
+hopsworks
+joblib
+scikit-learn