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import pickle
import numpy as np
import streamlit as st
from tensorflow.keras.models import load_model
import warnings

warnings.filterwarnings("ignore", category=UserWarning)

st.set_page_config(layout='wide')

def load_essential_models(scaler_6_path, scaler_8_path, scaler_full_path, clf_6_path, clf_8_path, clf_full_path):
    scaler_6 = pickle.load(open(file=scaler_6_path, mode='rb'))
    scaler_8 = pickle.load(open(file=scaler_8_path, mode='rb'))
    scaler_21 = pickle.load(open(file=scaler_full_path, mode='rb'))
    clf_6 = pickle.load(open(file=clf_6_path, mode='rb'))
    clf_8 = load_model(clf_8_path, compile=False)
    clf_21 = load_model(clf_full_path, compile=False)
    return scaler_6, scaler_8, scaler_21, clf_6, clf_8, clf_21

def convert_prediction(prediction):
    if prediction == [0]:
        return 'S'
    elif prediction == [1]:
        return 'M'
    else:
        return 'L'

st.markdown("<h1 style='text-align: center;'>Vietnamese Woman Bra Size Classifier</h1>", unsafe_allow_html=True)

scaler_6, scaler_8, scaler_21, clf_6, clf_8, clf_21 = load_essential_models(scaler_6_path='./Models/6/scaler.pkl', scaler_8_path='./Models/8/scaler.pkl', scaler_full_path='./Models/21/scaler.pkl', clf_6_path='./Models/6/svc_fs_tune.pkl', clf_8_path='./Models/8/ANN_8.h5', clf_full_path='./Models/21/ANNs_full.h5')

header_col_1, header_col_2 = st.columns([3, 2])
num_of_features = header_col_1.selectbox(label='Please select the number of measurements you have:', options=['6 measurements', '8 measurements', '21 measurements'])

# h, w, bmi, vtn, vn, vcn, cn, cnnp, cnnt, cntp, cntt, ccnp, ccnt, snt, sndp, sndt, xup, xut, cl, ttp, ttt = [0.0]*21

if num_of_features == '6 measurements':
    sample_options_6 = header_col_2.selectbox(label='Measurement sample options:', options=['Sample 1 (Small)', 'Sample 2 (Medium)', 'Sample 3 (Large)'])
    container_col_1, container_col_2, container_col_3 = st.columns([1, 1, 1])
    if sample_options_6 == 'Sample 1 (Small)':
        vtn = container_col_1.number_input(label='Upper bust circumference (cm):', value=82.00, min_value=0.00, step=0.01)
        vn = container_col_2.number_input(label='Bust circumference (cm):', value=82.40, min_value=0.00, step=0.01)
        vcn = container_col_3.number_input(label='Chest circumference (cm):', value=73.10, min_value=0.00, step=0.01)
        cl = container_col_1.number_input(label='Size difference (cm):', value=9.30, min_value=0.00, step=0.01)
        ttp = container_col_2.number_input(label='Volume of right breast (cm3):', value=325.6, min_value=0.00, step=0.01)
        ttt = container_col_3.number_input(label='Volume of left breast (cm3):', value=325.6, min_value=0.00, step=0.01)
    elif sample_options_6 == 'Sample 2 (Medium)':
        vtn = container_col_1.number_input(label='Upper bust circumference (cm):', value=77.20, min_value=0.00, step=0.01)
        vn = container_col_2.number_input(label='Bust circumference (cm):', value=78.60, min_value=0.00, step=0.01)
        vcn = container_col_3.number_input(label='Chest circumference (cm):', value=66.50, min_value=0.00, step=0.01)
        cl = container_col_1.number_input(label='Size difference (cm):', value=12.10, min_value=0.00, step=0.01)
        ttp = container_col_2.number_input(label='Volume of right breast (cm3):', value=388.80, min_value=0.00, step=0.01)
        ttt = container_col_3.number_input(label='Volume of left breast (cm3):', value=324.60, min_value=0.00, step=0.01)
    else:
        vtn = container_col_1.number_input(label='Upper bust circumference (cm):', value=86.50, min_value=0.00, step=0.01)
        vn = container_col_2.number_input(label='Bust circumference (cm):', value=88.00, min_value=0.00, step=0.01)
        vcn = container_col_3.number_input(label='Chest circumference (cm):', value=74.00, min_value=0.00, step=0.01)
        cl = container_col_1.number_input(label='Size difference (cm):', value=14.00, min_value=0.00, step=0.01)
        ttp = container_col_2.number_input(label='Volume of right breast (cm3):', value=451.30, min_value=0.00, step=0.01)
        ttt = container_col_3.number_input(label='Volume of left breast (cm3):', value=471.60, min_value=0.00, step=0.01)

elif num_of_features == '8 measurements':
    sample_options_8 = header_col_2.selectbox(label='Measurement sample options:', options=['Sample 1 (Small)', 'Sample 2 (Medium)', 'Sample 3 (Large)'])
    container_col_1, container_col_2, container_col_3, container_col_4 = st.columns([1, 1, 1, 1])
    if sample_options_8 == 'Sample 1 (Small)':
        ttp = container_col_1.number_input(label='Volume of right breast (cm3):', value=287.50, min_value=0.00, step=0.01)
        cl = container_col_2.number_input(label='Size difference (cm):', value=7.00, min_value=0.00, step=0.01)
        cnnp = container_col_3.number_input(label='Outer right breast curve (cm):', value=8.50, min_value=0.00, step=0.01)
        vn = container_col_4.number_input(label='Bust circumference (cm):', value=74.50, min_value=0.00, step=0.01)
        vtn = container_col_1.number_input(label='Upper bust circumference (cm):', value=74.00, min_value=0.00, step=0.01)
        cnnt = container_col_2.number_input(label='Outer left breast curve (cm):', value=8.90, min_value=0.00, step=0.01)
        cntp = container_col_3.number_input(label='Inner right breast curve (cm):', value=8.50, min_value=0.00, step=0.01)
        vcn = container_col_4.number_input(label='Chest circumference (cm):', value=67.50, min_value=0.00, step=0.01)
    elif sample_options_8 == 'Sample 2 (Medium)':
        ttp = container_col_1.number_input(label='Volume of right breast (cm3):', value=489.60, min_value=0.00, step=0.01)
        cl = container_col_2.number_input(label='Size difference (cm):', value=13.00, min_value=0.00, step=0.01)
        cnnp = container_col_3.number_input(label='Outer right breast curve (cm):', value=12.40, min_value=0.00, step=0.01)
        vn = container_col_4.number_input(label='Bust circumference (cm):', value=78.30, min_value=0.00, step=0.01)
        vtn = container_col_1.number_input(label='Upper bust circumference (cm):', value=77.20, min_value=0.00, step=0.01)
        cnnt = container_col_2.number_input(label='Outer left breast curve (cm):', value=11.60, min_value=0.00, step=0.01)
        cntp = container_col_3.number_input(label='Inner right breast curve (cm):', value=8.70, min_value=0.00, step=0.01)
        vcn = container_col_4.number_input(label='Chest circumference (cm):', value=65.30, min_value=0.00, step=0.01)
    else:
        ttp = container_col_1.number_input(label='Volume of right breast (cm3):', value=568.2, min_value=0.00, step=0.01)
        cl = container_col_2.number_input(label='Size difference (cm):', value=13.7, min_value=0.00, step=0.01)
        cnnp = container_col_3.number_input(label='Outer right breast curve (cm):', value=14.0, min_value=0.00, step=0.01)
        vn = container_col_4.number_input(label='Bust circumference (cm):', value=88.7, min_value=0.00, step=0.01)
        vtn = container_col_1.number_input(label='Upper bust circumference (cm):', value=86.5, min_value=0.00, step=0.01)
        cnnt = container_col_2.number_input(label='Outer left breast curve (cm):', value=12.5, min_value=0.00, step=0.01)
        cntp = container_col_3.number_input(label='Inner right breast curve (cm):', value=10.7, min_value=0.00, step=0.01)
        vcn = container_col_4.number_input(label='Chest circumference (cm):', value=75.0, min_value=0.00, step=0.01)
else:
    sample_options_21 = header_col_2.selectbox(label='Measurement sample options:', options=['Sample 1 (Small)', 'Sample 2 (Medium)', 'Sample 3 (Large)'])
    container_col_1, container_col_2, container_col_3, container_col_4, container_col_5 = st.columns([1, 1, 1, 1, 1])
    if sample_options_21 == 'Sample 1 (Small)':
        h = container_col_1.number_input(label='Height (cm):', value=158.50, min_value=0.00, step=0.01)
        w = container_col_2.number_input(label='Weight (kg):', value=44.00, min_value=0.00, step=0.01)
        bmi = container_col_3.number_input(label='BMI (kg/h^2):', value=17.50, min_value=0.00, step=0.01)
        vtn = container_col_4.number_input(label='Upper bust circumference (cm): ', value=75.40, min_value=0.00, step=0.01)
        vn = container_col_5.number_input(label='Bust circumference (cm):', value=81.10, min_value=0.00, step=0.01)
        vcn = container_col_1.number_input(label='Chest circumference (cm):', value=74.80, min_value=0.00, step=0.01)
        cn = container_col_2.number_input(label='Distance between nipple points (cm):', value=14.50, min_value=0.00, step=0.01)
        cnnp = container_col_3.number_input(label='Outer right breast curve (cm):', value=13.80, min_value=0.00, step=0.01)
        cnnt = container_col_4.number_input(label='Outer left breast curve (cm):', value=14.40, min_value=0.00, step=0.01)
        cntp = container_col_5.number_input(label='Inner right breast curve (cm):', value=8.60, min_value=0.00, step=0.01)
        cntt = container_col_1.number_input(label='Inner left breast curve (cm):', value=8.40, min_value=0.00, step=0.01)
        ccnp = container_col_2.number_input(label='Right breast curve (cm):', value=21.50, min_value=0.00, step=0.01)
        ccnt = container_col_3.number_input(label='Left breast curve (cm):', value=21.20, min_value=0.00, step=0.01)
        snt = container_col_4.number_input(label='Upper breast projection (cm):', value=8.90, min_value=0.00, step=0.01)
        sndp = container_col_5.number_input(label='Lower right breast projection (cm):', value=6.50, min_value=0.00, step=0.01)
        sndt = container_col_1.number_input(label='Lower left breast projection (cm):', value=6.50, min_value=0.00, step=0.01)
        xup = container_col_2.number_input(label='Distance from sternum to right nipple point (cm):', value=21.80, min_value=0.00, step=0.01)
        xut = container_col_3.number_input(label='Distance from sternum to left nipple point (cm):', value=21.10, min_value=0.00, step=0.01)
        cl = container_col_4.number_input(label='Size difference (cm):', value=6.30, min_value=0.00, step=0.01)
        ttp = container_col_5.number_input(label='Volume of right breast (cm3):', value=325.10, min_value=0.00, step=0.01)
        ttt = container_col_3.number_input(label='Volume of left breast (cm3):', value=335.70, min_value=0.00, step=0.01)
    elif sample_options_21 == 'Sample 2 (Medium)':
        h = container_col_1.number_input(label='Height (cm):',  value=163.00, min_value=0.00, step=0.01)
        w = container_col_2.number_input(label='Weight (kg):', value=43.00, min_value=0.00, step=0.01)
        bmi = container_col_3.number_input(label='BMI (kg/h^2):', value=16.20, min_value=0.00, step=0.01)
        vtn = container_col_4.number_input(label='Upper bust circumference (cm): ', value=76.00, min_value=0.00, step=0.01)
        vn = container_col_5.number_input(label='Bust circumference (cm):', value=79.00, min_value=0.00, step=0.01)
        vcn = container_col_1.number_input(label='Chest circumference (cm):', value=64.00, min_value=0.00, step=0.01)
        cn = container_col_2.number_input(label='Distance between nipple points (cm):', value=16.50, min_value=0.00, step=0.01)
        cnnp = container_col_3.number_input(label='Outer right breast curve (cm):', value=13.10, min_value=0.00, step=0.01)
        cnnt = container_col_4.number_input(label='Outer left breast curve (cm):', value=12.60, min_value=0.00, step=0.01)
        cntp = container_col_5.number_input(label='Inner right breast curve (cm):', value=9.20, min_value=0.00, step=0.01)
        cntt = container_col_1.number_input(label='Inner left breast curve (cm):', value=9.10, min_value=0.00, step=0.01)
        ccnp = container_col_2.number_input(label='Right breast curve (cm):', value=19.80, min_value=0.00, step=0.01)
        ccnt = container_col_3.number_input(label='Left breast curve (cm):', value=18.20, min_value=0.00, step=0.01)
        snt = container_col_4.number_input(label='Upper breast projection (cm):', value=8.40, min_value=0.00, step=0.01)
        sndp = container_col_5.number_input(label='Lower right breast projection (cm):', value=3.50, min_value=0.00, step=0.01)
        sndt = container_col_1.number_input(label='Lower left breast projection (cm):', value=3.70, min_value=0.00, step=0.01)
        xup = container_col_2.number_input(label='Distance from sternum to right nipple point (cm):', value=21.00, min_value=0.00, step=0.01)
        xut = container_col_3.number_input(label='Distance from sternum to left nipple point (cm):', value=20.50, min_value=0.00, step=0.01)
        cl = container_col_4.number_input(label='Size difference (cm):', value=15.00, min_value=0.00, step=0.01)
        ttp = container_col_5.number_input(label='Volume of right breast (cm3):',  value=521.60, min_value=0.00, step=0.01)
        ttt = container_col_3.number_input(label='Volume of left breast (cm3):',  value=513.50, min_value=0.00, step=0.01)
    else:
        h = container_col_1.number_input(label='Height (cm):', value=152.00, min_value=0.00, step=0.01)
        w = container_col_2.number_input(label='Weight (kg):', value=46.00, min_value=0.00, step=0.01)
        bmi = container_col_3.number_input(label='BMI (kg/h^2):', value=19.90, min_value=0.00, step=0.01)
        vtn = container_col_4.number_input(label='Upper bust circumference (cm): ', value=77.50, min_value=0.00, step=0.01)
        vn = container_col_5.number_input(label='Bust circumference (cm):', value=85.50, min_value=0.00, step=0.01)
        vcn = container_col_1.number_input(label='Chest circumference (cm):', value=70.40, min_value=0.00, step=0.01)
        cn = container_col_2.number_input(label='Distance between nipple points (cm):', value=18.90, min_value=0.00, step=0.01)
        cnnp = container_col_3.number_input(label='Outer right breast curve (cm):', value=13.50, min_value=0.00, step=0.01)
        cnnt = container_col_4.number_input(label='Outer left breast curve (cm):', value=12.50, min_value=0.00, step=0.01)
        cntp = container_col_5.number_input(label='Inner right breast curve (cm):', value=10.30, min_value=0.00, step=0.01)
        cntt = container_col_1.number_input(label='Inner left breast curve (cm):', value=10.50, min_value=0.00, step=0.01)
        ccnp = container_col_2.number_input(label='Right breast curve (cm):', value=20.40, min_value=0.00, step=0.01)
        ccnt = container_col_3.number_input(label='Left breast curve (cm):', value=20.10, min_value=0.00, step=0.01)
        snt = container_col_4.number_input(label='Upper breast projection (cm):', value=8.50, min_value=0.00, step=0.01)
        sndp = container_col_5.number_input(label='Lower right breast projection (cm):', value=5.50, min_value=0.00, step=0.01)
        sndt = container_col_1.number_input(label='Lower left breast projection (cm):', value=4.20, min_value=0.00, step=0.01)
        xup = container_col_2.number_input(label='Distance from sternum to right nipple point (cm):', value=19.50, min_value=0.00, step=0.01)
        xut = container_col_3.number_input(label='Distance from sternum to left nipple point (cm):', value=20.50, min_value=0.00, step=0.01)
        cl = container_col_4.number_input(label='Size difference (cm):', value=15.10, min_value=0.00, step=0.01)
        ttp = container_col_5.number_input(label='Volume of right breast (cm3):', value=625.80, min_value=0.00, step=0.01)
        ttt = container_col_3.number_input(label='Volume of left breast (cm3):', value=585.40, min_value=0.00, step=0.01)

col_1, col_2, col_3, col_4, col_5 = st.columns([1, 1, 1, 1, 1])

with col_3:
    predict = st.button(label='Predict', use_container_width=True)

if predict:
    if num_of_features == '6 measurements':
        X_6 = np.array([[vtn, vn, vcn, cl, ttp, ttt]])
        X_6 = scaler_6.transform(X_6)
        y_6 = clf_6.predict(X_6)
        st.success(f'We recommend you choosing **{convert_prediction(y_6)}** size!')
    elif num_of_features == '8 measurements':
        X_8 = np.array([[ttp, cl, cnnp, vn, vtn, cnnt, cntp, vcn]])
        X_8 = scaler_8.transform(X_8)
        y_8 = clf_8.predict(X_8)
        st.success(f'We recommend you choosing **{convert_prediction(np.argmax(y_8, axis=1))}** size!')
    else:
        X_21 = np.array([[h, w, bmi, vtn, vn, vcn, cn, cnnp, cnnt, cntp, cntt, ccnp, ccnt, snt, sndp, sndt, xup, xut, cl, ttp, ttt]])
        X_21 = scaler_21.transform(X_21)
        y_21 = clf_21.predict(X_21)
        st.success(f'We recommend you choosing **{convert_prediction(np.argmax(y_21, axis=1))}** size!')