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## Alternative movie poster generator
import streamlit as st
import pandas as pd
import numpy as np
import json
import requests
import os
import io
from streamlit import session_state as session
from datetime import time, datetime
from zipfile import ZipFile
from htbuilder import HtmlElement, div, ul, li, br, hr, a, p, img, styles, classes, fonts
from htbuilder.units import percent, px
from htbuilder.funcs import rgba, rgb
from PIL import Image
###############################
## --- GLOBAL VARIABLES ---- ##
###############################
PATH_JSON = '/home/user/.kaggle/kaggle.json'
# Environment variables to authenticate Kaggle account
os.environ['KAGGLE_USERNAME'] = st.secrets['username']
os.environ['KAGGLE_KEY'] = st.secrets['key']
os.environ['KAGGLE_CONFIG_DIR'] = PATH_JSON
from kaggle.api.kaggle_api_extended import KaggleApi
###############################
## ------- FUNCTIONS ------- ##
###############################
def link(link, text, **style):
return a(_href=link, _target="_blank", style=styles(**style))(text)
def image(src_as_string, **style):
return img(src=src_as_string, style=styles(**style))
def layout(*args):
style = """
<style>
# MainMenu {visibility: hidden;}
footer {visibility: hidden;}
.stApp { bottom: 105px; }
</style>
"""
style_div = styles(
position="fixed",
left=0,
bottom=0,
margin=px(0, 0, 0, 0),
width=percent(100),
color="black",
text_align="center",
height="auto",
opacity=1
)
style_hr = styles(
display="block",
margin=px(8, 8, "auto", "auto"),
border_style="inset",
border_width=px(2)
)
body = p()
foot = div(
style=style_div
)(
hr(
style=style_hr
),
body
)
st.markdown(style, unsafe_allow_html=True)
for arg in args:
if isinstance(arg, str):
body(arg)
elif isinstance(arg, HtmlElement):
body(arg)
st.markdown(str(foot), unsafe_allow_html=True)
def footer():
myargs = [
#"Made in ",
#image('https://avatars3.githubusercontent.com/u/45109972?s=400&v=4',
# width=px(25), height=px(25)),
#" with ❤️ by ",
"Made with ❤️ by ",
link("https://www.linkedin.com/in/gaspar-avit/", "Gaspar Avit"),
]
layout(*myargs)
def authenticate_kaggle():
# Connect to kaggle API
# Save credentials to json file
if not os.path.exists(PATH_JSON):
api_token = {"username":st.secrets['username'],"key":st.secrets['key']}
with open(PATH_JSON, 'w') as file:
json.dump(api_token, file)
# Activate Kaggle API
global api
api = KaggleApi()
api.authenticate()
@st.experimental_memo(persist=True, show_spinner=False, suppress_st_warning=True)
def load_dataset():
"""
Load Dataset from Kaggle
-return: dataframe containing dataset
"""
## --- Connect to kaggle API --- ##
# Save credentials to json file
if not os.path.exists(PATH_JSON):
api_token = {"username":st.secrets['username'],"key":st.secrets['key']}
with open(PATH_JSON, 'w') as file:
json.dump(api_token, file)
# Activate Kaggle API
global api
api = KaggleApi()
api.authenticate()
## ----------------------------- ##
# Downloading Movies dataset
api.dataset_download_file('rounakbanik/the-movies-dataset', 'movies_metadata.csv')
# Extract data
zf = ZipFile('movies_metadata.csv.zip')
zf.extractall()
zf.close()
# Create dataframe
data = pd.read_csv('movies_metadata.csv', low_memory=False)
data.drop_duplicates(inplace=True)
return data
def query_summary(text):
"""
Get summarization from HuggingFace Inference API
-param text: text to be summarized
-return: summarized text
"""
API_URL = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn"
headers = {"Authorization": f"Bearer {st.secrets['hf_token']}"}
payload = {"inputs": f"{text}",}
response = requests.request("POST", API_URL, headers=headers, json=payload).json()
try:
text = response[0].get('summary_text')
except:
text = response[0]
return text
def query_generate(text):
"""
Get image from HuggingFace Inference API
-param text: text to generate image
-return: generated image
"""
API_URL = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"
headers = {"Authorization": f"Bearer {st.secrets['hf_token']}"}
payload = {"inputs": f"{text}",}
response = requests.post(API_URL, headers=headers, json=payload)
return response.content
def generate_poster(movie_data):
"""
Function for recommending movies
-param movie_data: metadata of movie selected by user
-return: image of generated alternative poster
"""
# Get summarization of movie synopsis
with st.spinner("Please wait while the synopsis is being summarized..."):
synopsis_sum = query_summary(movie_data.overview.values[0])
st.text("")
st.text("")
st.text("Synopsis summary: " + synopsis_sum)
# Get image based on synopsis
with st.spinner("Generating poster image..."):
poster_image = query_generate(synopsis_sum)
# Show image
try:
image = Image.open(io.BytesIO(poster_image))
st.image(image, caption="Movie: " + movie_data.title.values[0])
except:
st.text(poster_image)
return poster_image
# ------------------------------------------------------- #
###############################
## --------- MAIN ---------- ##
###############################
if __name__ == "__main__":
# Initialize image variable
image = None
## --- Page config ------------ ##
# Set page title
st.title("""
Movie Poster Generator :film_frames:
#### This is a movie poster generator based on movie's synopsis :sunglasses:
#### Just select the title of a movie to generate an alternative poster.
""")
# Set page footer
footer()
## ---------------------------- ##
## Create dataset
data = load_dataset()
st.text("")
st.text("")
st.text("")
st.text("")
selected_movie = st.selectbox(label="Select a movie to generate alternative poster", options=data.title)
st.text("")
st.text("")
buffer1, col1, col2, buffer2 = st.columns([1.3, 1, 1, 1])
is_clicked_1 = col1.button(label="Generate poster!")
if is_clicked_1:
generate_poster(data[data.title==selected_movie])
if st.button('Reset', False):
st.empty()
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