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3d2fc57 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | # -*- coding: utf-8 -*-
"""app.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1QDGbOvpwcdGFAUHlqUqKjWG_UkARrh_A
"""
import joblib
import pandas as pd
import streamlit as st
SPC_DICT = {'setosa': 0,
'versicolor': 1,
'virginica': 2
}
model = joblib.load('model.joblib')
unique_values = joblib.load('unique_values.joblib')
#unique_srecies = unique_values["srecies"]
unique_sepal_length = unique_values["sepal_length"]
unique_sepal_width = unique_values["sepal_width"]
unique_petal_length = unique_values["petal_length"]
unique_petal_width = unique_values["petal_width"]
def main():
st.title("Iris")
with st.form("questionnaire"):
sepal_length = st.slider("sepal_length", min_value=0, max_value=20)
sepal_width = st.slider("sepal_width", min_value=0, max_value=20)
petal_length = st.slider("petal_length", min_value=0, max_value=20)
petal_width = st.slider("petal_width", min_value=0, max_value=20)
clicked = st.form_submit_button("Predict iris")
if clicked:
result = model.predict(pd.DataFrame({
"sepal_length": [sepal_length],
"sepal_width": [sepal_width],
"petal_length": [petal_length],
"petal_width": [petal_width]
}))
result = 'setosa' if result[0] == 0 result = 'versicolor' elif result[0] == 1 else result = 'virginica'
st.success('The predicted iris is {}'.format(result))
if __name__ == '__main__':
main() |