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import gradio as gr |
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import numpy as np |
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from PIL import Image |
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import requests |
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import hopsworks |
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import joblib |
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project = hopsworks.login() |
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fs = project.get_feature_store() |
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mr = project.get_model_registry() |
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model = mr.get_model("titanic_survival_modal", version=1) |
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model_dir = model.download() |
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model = joblib.load(model_dir + "/titanic_survival_model.pkl") |
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def titanic(pclass, sex, age, fare, embarked, title, isalone): |
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input_list = [] |
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input_list.append(int(pclass+1)) |
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input_list.append(int(sex)) |
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if age<=16: |
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input_list.append(0) |
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elif age>16 and age<=32: |
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input_list.append(1) |
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elif age>32 and age<=48: |
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input_list.append(2) |
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elif age>48 and age<=64: |
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input_list.append(3) |
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else: |
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input_list.append(4) |
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if fare<=7.91: |
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input_list.append(0) |
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elif fare>7.91 and fare<=14.454: |
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input_list.append(1) |
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elif fare>14.454 and fare<=31: |
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input_list.append(2) |
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else: |
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input_list.append(3) |
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if embarked=='C': |
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input_list.append(1) |
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elif embarked=='S': |
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input_list.append(0) |
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else: |
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input_list.append(2) |
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input_list.append(title) |
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input_list.append(isalone) |
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res = model.predict(np.asarray(input_list,dtype=object).reshape(1,-1)) |
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if res[0] == 0: |
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person="dead" |
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passenger_url = "https://raw.githubusercontent.com/irena123333/titanic-prediction/main/dead.png" |
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else: |
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person="survived" |
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passenger_url = "https://raw.githubusercontent.com/irena123333/titanic-prediction/main/survived.png" |
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img = Image.open(requests.get(passenger_url, stream=True).raw) |
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return img |
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demo = gr.Interface( |
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fn=titanic, |
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title="Titanic Passenger Survival Predictive Analytics", |
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description="If one person is on titanic, predict whether he or she will survive.", |
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allow_flagging="never", |
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inputs=[gr.inputs.Dropdown(choices=["Class 1","Class 2","Class 3"], type="index", label="pclass"), |
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gr.inputs.Dropdown(choices=["Male", "Female"], type="index", label="sex"), |
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gr.inputs.Slider(0,150,label='Age'), |
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gr.inputs.Number(default=8.0, label="Fare"), |
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gr.inputs.Radio(default='S', label="Embarkation Port", choices=['C', 'Q', 'S']), |
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gr.inputs.Dropdown(choices=["Master","Miss","Mr","Mrs","Other"], type="index", label="Title"), |
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gr.inputs.Dropdown(choices=["False", "True"], type="index", label="IsAlone"), |
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], |
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outputs=gr.Image(type="pil")) |
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demo.launch() |
