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Runtime error
Hope-Liang
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Commit
•
fe65d04
1
Parent(s):
7caf538
update
Browse files- README.md +5 -5
- app.py +84 -0
- requirements.txt +3 -0
README.md
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---
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title:
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emoji:
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colorFrom:
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sdk: gradio
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sdk_version: 3.
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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title: Iris
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emoji: 🐢
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colorFrom: purple
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colorTo: green
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sdk: gradio
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sdk_version: 3.5
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app_file: app.py
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pinned: false
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license: apache-2.0
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app.py
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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_modal", version=1)
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model_dir = model.download()
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model = joblib.load(model_dir + "/titanic_model.pkl")
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def titanic(pclass, sex, age, sibsp, parch, fare, embarked):
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input_list = []
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if sex == 'female':
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input_list.append(1.0)
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input_list.append(0.0)
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elif sex == 'male':
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input_list.append(0.0)
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input_list.append(1.0)
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else:
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print("ERROR!")
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exit()
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if embarked = "C":
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input_list.append(1.0)
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input_list.append(0.0)
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input_list.append(0.0)
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elif embarked = "Q":
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input_list.append(0.0)
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input_list.append(1.0)
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input_list.append(0.0)
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elif embarked = "S":
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input_list.append(0.0)
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input_list.append(0.0)
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input_list.append(1.0)
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else:
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print("ERROR!")
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exit()
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if age < 18:
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input_list.append(1.0)
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elif age < 55:
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input_list.append(2.0)
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else:
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input_list.append(3.0)
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input_list.append(sibsp)
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input_list.append(parch)
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input_list.append(fare)
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input_list.append(pclass)
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# 'res' is a list of predictions returned as the label.
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res = model.predict(np.asarray(input_list).reshape(1, -1))
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# We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want
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# the first element.
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if res[0] == 1.0:
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survive_url = "https://raw.githubusercontent.com/Hope-Liang/ID2223Lab1/main/serverless-ml-titanic/images/survived.png"
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else:
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survive_url = "https://raw.githubusercontent.com/Hope-Liang/ID2223Lab1/main/serverless-ml-titanic/images/died.png"
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img = Image.open(requests.get(survive_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 Survival Predictive Analytics",
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description="Experiment with titanic passenger features to predict whether survived or not.",
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allow_flagging="never",
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inputs=[
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gr.inputs.Number(default=1, label="Pclass (1,2,3)")
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gr.inputs.Textbox(default="female", label="Sex (female/male)"),
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gr.inputs.Number(default=30.0, label="age (years)"),
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gr.inputs.Number(default=1.0, label="SibSp"),
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gr.inputs.Number(default=1.0, label="Parch"),
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gr.inputs.Number(default=10.0, label="Fare (GBP)")
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gr.inputs.Textbox(default="S", label="Embarked (S,C,Q)")
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],
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outputs=gr.Image(type="pil"))
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demo.launch()
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requirements.txt
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hopsworks
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joblib
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scikit-learn
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