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9303e53
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Parent(s):
8bba14b
Upload 2 files
Browse files- app.py +86 -0
- requirements.txt +3 -0
app.py
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#!/usr/bin/env python
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# coding: utf-8
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# In[1]:
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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("tita_modal", version=1)
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model_dir = model.download()
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model = joblib.load(model_dir + "/tita_model.pkl")
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def tita(passengerid, age, sibsp, parch, fare, cabin_no, cabin_yes, embarked_c, embarked_q, embarked_s, sex_female, sex_male, pclass_1, pclass_2, pclass_3):
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input_list = []
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input_list.append(passengerid)
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input_list.append(age)
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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(cabin_no)
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input_list.append(cabin_yes)
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input_list.append(embarked_c)
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input_list.append(embarked_q)
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input_list.append(embarked_s)
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input_list.append(sex_female)
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input_list.append(sex_male)
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input_list.append(pclass_1)
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input_list.append(pclass_2)
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input_list.append(pclass_3)
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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):
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life = "alive"
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else:
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life = "dead"
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flower_url = "https://raw.githubusercontent.com/Man-bearpig/ID2223/main/" + life + ".png"
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img = Image.open(requests.get(flower_url, stream=True).raw)
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return img
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demo = gr.Interface(
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fn=tita,
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title="titanic",
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description="Experiment with sepal/petal lengths/widths to predict which flower it is.",
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allow_flagging="never",
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inputs=[
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gr.inputs.Number(default=1.0, label="passengerid"),
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gr.inputs.Number(default=1.0, label="age"),
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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=1.0, label="fare"),
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gr.inputs.Number(default=1.0, label="cabin_no"),
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gr.inputs.Number(default=1.0, label="cabin_yes"),
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gr.inputs.Number(default=1.0, label="embarked_c"),
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gr.inputs.Number(default=1.0, label="embarked_q"),
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gr.inputs.Number(default=1.0, label="embarked_s"),
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gr.inputs.Number(default=1.0, label="sex_female"),
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gr.inputs.Number(default=1.0, label="sex_male"),
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gr.inputs.Number(default=1.0, label="pclass_1"),
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gr.inputs.Number(default=1.0, label="pclass_2"),
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gr.inputs.Number(default=1.0, label="pclass_3"),
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],
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outputs=gr.Image(type="pil"))
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demo.launch()
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# In[ ]:
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requirements.txt
ADDED
@@ -0,0 +1,3 @@
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hopsworks
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joblib
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scikit-learn
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