rev_map = {0: 'BERHI',
 1: 'DEGLET',
 2: 'DOKOL',
 3: 'IRAQI',
 4: 'ROTANA',
 5: 'SAFAVI',
 6: 'SOGAY'}
import streamlit as st
import joblib

st.title('Dates Type Classification App')

st.write('This app takes in the features and classifies the date')

st.image('pic.jpg')

model  = joblib.load('log_model.pkl')
scaler = joblib.load('scaler.pkl')

#['AREA', 'PERIMETER', 'MINOR_AXIS', 'CONVEX_AREA', 'ROUNDNESS', 'MeanRR',
#       'SkewRR', 'SkewRB', 'EntropyRG', 'ALLdaub4RR']


area = st.number_input('Enter area:')
perimeter = st.number_input('Enter perimeter:')
minor_axis = st.number_input('Enter minor_axis:')
convex_area = st.number_input('Enter convex_area:')
roundness = st.number_input('Enter roundness:')
meanrr = st.number_input('Enter meanrr:')
skewrr = st.number_input('Enter skewrr:')
skewrb = st.number_input('Enter skewrb:')
entropyrg = st.number_input('Enter entropyrg:')
ALLdaub4RR = st.number_input('Enter ALLdaub4RR:')



if st.button('Predict:--->'):
	sample = [[area,perimeter,minor_axis,convex_area,roundness,meanrr,skewrr,skewrb,entropyrg,ALLdaub4RR]]
	sample_scaled = scaler.transform(sample)
	pred = model.predict(sample_scaled)
	st.write(f"The class is : {rev_map[pred[0]]}")