TE_MINIPROJECT_2/admin_predict_page.py at main · parth3102/TE_MINIPROJECT_2 · GitHub

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import streamlit as st
import pickle
import numpy as np


def load_model():
    with open('saved_steps1.pkl', 'rb') as file:
        data = pickle.load(file)
    return data


data = load_model()

model = data["model"]
le_state = data["le_state"]
le_temp = data["le_temp"]
le_ph = data["le_ph"]
le_bod = data["le_bod"]
le_ni = data["le_ni"]


def show_predict_page1():
    st.title("Water Quality Prediction")

    st.write("""### We built a model to predict the average water quality of your state's water reservoirs""")
    states = (
        "RAJASTHAN",
        "GUJARAT",
        "BIHAR",
        "ASSAM",
        "ODISHA",
        "WEST BENGAL",
        "MADHYA PRADESH",
        "Other",
        "TRIPURA",
        "PUNJAB",
        "MAHARASHTRA",
        "KERALA",
        "TELANGANA",
        "HIMACHAL PRADESH",
        "UTTAR PRADESH",
        "ANDHRA PRADESH",
        "LAKSHADWEEP",
        "DELHI",
        "MIZORAM",
        "PUDUCHERRY",
        "UTTARAKHAND",
        "NAGALAND",
        "TAMIL NADU",
        "GOA",
        "MEGHALAYA",
        "CHHATTISGARH"
    )

    state = st.selectbox("State", states)
    temp = st.slider("Temperature in celcius", 0, 39)
    ph = st.number_input("PH", 4.0, 10.0, 7.0, step=0.1)
    bod = st.number_input("BOD", 0.0, 10.0, 1.7, step=0.1)
    ni = st.number_input("NI", 0.0, 4.0, 2.4, step=0.2)

    ok = st.button("Predict Quality")
    if ok:
        X = np.array([[state, temp, ph, bod, ni]])
        X[:, 0] = le_state.transform(X[:, 0])
        X[:, 1] = le_temp.transform(X[:, 1])
        X[:, 2] = le_ph.transform(X[:, 2])
        X[:, 3] = le_bod.transform(X[:, 3])
        X[:, 4] = le_ni.transform(X[:, 4])
        X = X.astype(float)

        quality = model.predict(X)
        if quality == 0:
            st.subheader(
                f"The predicted quality is VERY POOR! You are strongly adviced not to consume it")
        if quality > 0 and quality <= 1:
            st.subheader(f"The predicted quality is Poor but can be drinkable if you follow the following steps:\n"
                         "1. Boiling and Filtering by filter paper\n"
                         "2. Bleach Disinfection\n"
                         "3. Disinfect through chlorine dioxide tablets")
        if quality > 1 and quality <= 1.5:
            st.subheader(
                f"The predicted quality is Good and you can drink it by simply boiling it")
        if quality > 1.5:
            st.subheader(
                f"The predicted quality is Excellent and you can drink it directly")