import os
import streamlit as st
import autotab.TabPrediction as tp
import pandas as pd
import numpy as np 
from autotab.TabDataReprGen import TabDataReprGen
from PIL import Image

st.set_page_config(
    page_title="AutoTab tab generator",
    layout="centered", # centered
    initial_sidebar_state="auto") # collapsed

image_path = "https://images.unsplash.com/photo-1535587566541-97121a128dc5?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=870&q=80"
st.write(f'<div class="banner" style="background-image: linear-gradient(rgba(0,0,0,0.4),rgba(0,0,0,0.4)), url({image_path});"><h1>Autotab</h1><p>Learning the guitar the easy way</p></div>', unsafe_allow_html=True)
CSS = """
.banner {
    background-position: center;
    background-repeat: no-repeat;
    background-size: cover;
    position: relative;
    height: 300px;
    text-align: center;
    margin-top: -100px;
    margin-left: -480px;
    margin-right: -480px;
}
.banner h1 {
    padding-top: 120px;
    margin: 0;
    color: white;
    text-shadow: 1px 1px 3px rgba(0,0,0,0.2);
    font-size: 56px;
    font-weight: bold;
}
.banner p {
    font-size: 32px;
    color: white;
    opacity: .7;
    text-shadow: 1px 1px 3px rgba(0,0,0,0.2);
}
"""
st.write(f'<style>{CSS}</style>', unsafe_allow_html=True)


st.set_option('deprecation.showfileUploaderEncoding', False)

uploaded_file = st.file_uploader("choose a music file:", type="wav")

processed_file = None

mode = st.radio('Choose Mode of Tab production:', ('Ergonomic Simple', 'Ergonomic Rhythm', 'All Frames'))
st.write('<style>div.row-widget.stRadio > div{flex-direction:row;}</style>', unsafe_allow_html=True)

###########################################################
# slider for number of divisions 

num_div = st.slider('Select number of frets per line', 1, 10, 3)
# web_tabs(tabs, num_div=4, len_div=16)

###########################################################

model = tp.load_model_and_weights()
model.load_weights('./h5-model/full_val0_75acc_weights.h5')
genrep = TabDataReprGen()

if uploaded_file is not None:
    x_new = genrep.load_rep_from_raw_file(uploaded_file)
    y_pred = model.predict(x_new)
    processed_file= uploaded_file
    
if uploaded_file is not None and mode == 'Ergonomic Simple': 
    st.title("""
            Ergonomic Simple predicted Tabs: 
    """)
    if uploaded_file != processed_file:        
        x_new = genrep.load_rep_from_raw_file(uploaded_file)
        # st.write(x_new.shape)
        y_pred = model.predict(x_new)
        processed_file = uploaded_file
    
    all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
    simple_tabs = tp.make_squeezed_tab(all_frames_tab)
    simple_text = tp.web_tabs(simple_tabs)
    st.text(simple_text)
    
if uploaded_file is not None and mode == 'Ergonomic Rhythm': 
    st.title("""
            Ergonomic Rhythm predicted Tabs:
    """)
    if uploaded_file != processed_file:        
        x_new = genrep.load_rep_from_raw_file(uploaded_file)
        # st.write(x_new.shape)
        y_pred = model.predict(x_new)
        processed_file = uploaded_file
    
    all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
    rythm_tabs = tp.make_dynamic_tab(all_frames_tab)
    rythm_text = tp.web_tabs(rythm_tabs)
    st.text(rythm_text)
    
if uploaded_file is not None and mode == 'All Frames': 
    st.title("""
            All Frames predicted Tabs:
    """)
    if uploaded_file != processed_file:        
        x_new = genrep.load_rep_from_raw_file(uploaded_file)
        # st.write(x_new.shape)
        y_pred = model.predict(x_new)
        processed_file = uploaded_file
    

    all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
    ################################################
    # all_frames_tab.to_csv('all_frames_tab.csv')
    ################################################
    all_frames_text = tp.web_tabs(all_frames_tab)
    st.text(all_frames_text)