Create app.py

app.py

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+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, age, sibsp, parch, fare, embarked, pclass): #check if the order is the same in the feature hopsworks
+    input_list = []
+    input_list.append(sex)
+    input_list.append(age)
+    input_list.append(sibsp)
+    input_list.append(parch)
+    input_list.append(fare)
+    if embarked == 1:
+        input_list.append(1) 
+        input_list.append(0)
+        input_list.append(0)
+    elif embarked == 2:
+        input_list.append(0) 
+        input_list.append(1)
+        input_list.append(0)
+    else:
+        input_list.append(0) 
+        input_list.append(0)
+        input_list.append(1)
+
+    if pclass == 1:
+        input_list.append(1) 
+        input_list.append(0)
+        input_list.append(0)
+    elif pclass == 2:
+        input_list.append(0) 
+        input_list.append(1)
+        input_list.append(0)
+    else:
+        input_list.append(0) 
+        input_list.append(0)
+        input_list.append(1)
+        
+    # '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:
+       image_url = "https://i.ibb.co/0X0JTcx/survive.jpg"
+    else:
+       image_url = "https://i.ibb.co/C8SdRn2/drowning.jpg"
+    img = Image.open(requests.get(image_url, stream=True).raw)            
+    return img
+    #return res[0]
+        
+demo = gr.Interface(
+    fn=titanic,
+    title="Titanic Predictive Analytics",
+    description="Experiment with titanic dataset to predicte if a passenger is survived or not",
+    allow_flagging="never",
+    inputs=[
+        gr.inputs.Number(default=1.0, label="sex"),
+        gr.inputs.Number(default=1.0, label="age"),
+        gr.inputs.Number(default=1.0, label="sibsp"),
+        gr.inputs.Number(default=1.0, label="parch"),
+        gr.inputs.Number(default=1.0, label="fare"),
+        gr.inputs.Number(default=1.0, label="embarked"),
+        gr.inputs.Number(default=1.0, label="pclass"),
+        ],
+    outputs=gr.Image(type="pil"))
+    #outputs = "number"
+demo.launch(debug=True)