app.py

import neural_style

import streamlit as st
import numpy as np
import cv2
from  PIL import Image, ImageEnhance

#Create two columns with different width
col1, col2 = st.columns( [0.8, 0.2])
with col1:               # To display the header text using css style
    st.markdown(""" <style> .font {
    font-size:35px ; font-family: 'Cooper Black'; color: #FF9633;} 
    </style> """, unsafe_allow_html=True)
    st.markdown('<p class="font">Upload your photo here...</p>', unsafe_allow_html=True)
    
#Add a header and expander in side bar
st.sidebar.markdown('<p class="font">Afrodreams.AI</p>', unsafe_allow_html=True)
with st.sidebar.expander("About the App"):
     st.write("""
        This app takes in your image and styles it with a unique african art.""")

#Add file uploader to allow users to upload photos
uploaded_file = st.file_uploader("", type=['jpg','png','jpeg'])

#Add 'before' and 'after' columns
if uploaded_file is not None:
    image = Image.open(uploaded_file)
    
    col1, col2 = st.columns( [0.5, 0.5])
    with col1:
        st.markdown('<p style="text-align: center;">Before</p>',unsafe_allow_html=True)
        st.image(image,width=300)  

    with col2:
        st.markdown('<p style="text-align: center;">After</p>',unsafe_allow_html=True)
        
    # add a button
    run = st.button('Generate Art')
    if run==True:
        params = neural_style.TransferParams()
        params.gpu = "c"
        params.backend = "mkl"
        params.image_size = 128
        params.content_image = uploaded_file
        neural_style.transfer(params)

        #display image when done.
        with col2:
            result = Image.open('out.png')
            st.image(result, width=300)
            run =st.download_button(label="Download Image", data=result.tobytes(), file_name='afrodreams.png')



#img = neural_style.transfer(params)