Initial commit

app.py

@@ -0,0 +1,52 @@
+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, Pclass, Fare, Parch, SibSp, Embarked):
+ input_list = []
+ input_list.append(Sex)
+ input_list.append(Age)
+ input_list.append(Pclass)
+ input_list.append(Fare)
+ input_list.append(Parch)
+ input_list.append(SibSp)
+ input_list.append(Embarked)
+ # '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.
+ pic_url = "https://raw.githubusercontent.com/backgroundhumeur/id2223_labs/main/src/titanic/assets/titanic_" + res[0] + ".jpg"
+ img = Image.open(requests.get(pic_url, stream=True).raw)
+ return img
+
+demo = gr.Interface(
+ fn=titanic,
+ title="Titanic Passenger Survival Predictive Analytics",
+ description="Experiment with different characteristics of a passenger to predict whether he would have survived if he were aboard the titanic.",
+ allow_flagging="never",
+ inputs=[
+ gr.inputs.Dropdown(choices=["male","female"], value="male", label="Sex"),
+ gr.inputs.Number(default=28.0, label="Age", precision=0),
+ gr.inputs.Slider(minimum=1.0,maximum=3.0,value=3.0,step=1.0, label="Ticket class (1st to 3rd)"),
+ gr.inputs.Number(default=14.4542, label="Fare ($)"),
+ gr.inputs.Number(default=0.0, label="Number of parents/children aboard", precision=0),
+ gr.inputs.Number(default=0.0, label="Number of siblings/spouses aboard", precision=0),
+ gr.inputs.Dropdown(choices=["S","C", "Q"], value="C", label="Port of Embarkation")
+ ],
+ outputs=gr.Image(type="pil"))
+
+demo.launch()