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app.py
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import neural_style
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import streamlit as st
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import numpy as np
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import cv2
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from PIL import Image, ImageEnhance
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#Create two columns with different width
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col1, col2 = st.columns( [0.8, 0.2])
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with col1: # To display the header text using css style
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st.markdown(""" <style> .font {
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font-size:35px ; font-family: 'Cooper Black'; color: #FF9633;}
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</style> """, unsafe_allow_html=True)
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st.markdown('<p class="font">Upload your photo here...</p>', unsafe_allow_html=True)
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#Add a header and expander in side bar
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st.sidebar.markdown('<p class="font">Afrodreams.AI</p>', unsafe_allow_html=True)
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with st.sidebar.expander("About the App"):
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st.write("""
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This app takes in your image and styles it with a unique african art.""")
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#Add file uploader to allow users to upload photos
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uploaded_file = st.file_uploader("", type=['jpg','png','jpeg'])
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#Add 'before' and 'after' columns
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if uploaded_file is not None:
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image = Image.open(uploaded_file)
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col1, col2 = st.columns( [0.5, 0.5])
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with col1:
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st.markdown('<p style="text-align: center;">Before</p>',unsafe_allow_html=True)
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st.image(image,width=300)
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with col2:
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st.markdown('<p style="text-align: center;">After</p>',unsafe_allow_html=True)
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# add a button
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run = st.button('Generate Art')
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if run==True:
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params = neural_style.TransferParams()
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params.gpu = "c"
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params.backend = "mkl"
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params.image_size = 128
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params.content_image = uploaded_file
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neural_style.transfer(params)
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#display image when done.
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with col2:
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result = Image.open('out.png')
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st.image(result, width=300)
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run =st.download_button(label="Download Image", data=result.tobytes(), file_name='afrodreams.png')
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#img = neural_style.transfer(params)
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