Upload app.py

app.py

@@ -1,3 +1,297 @@
+## 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)
+
+    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.title("""
+        #### Synopsis: """)
+    st.text("Synopsis summary: " + synopsis_sum)
+    st.text("")
+
+
+    # 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.text("")
+        st.text("")
+        st.title("""
+            #### Resulting poster: """)
+        col1, col2, col3 = st.columns(3)
+
+        with col1:
+            st.write(' ')
+
+        with col2:
+            st.text("")
+            st.image(image, caption="Movie: \"" + movie_data.title.values[0] + "\"")
+
+        with col3:
+            st.write(' ')
+
+    except:
+        st.text(poster_image)
+
+
+    return poster_image
+# ------------------------------------------------------- #
+
+
+###############################
+## --------- MAIN ---------- ##
+###############################
+
+
+if __name__ == "__main__":
+
+
+    # Initialize image variable
+    poster = 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, buffer2 = st.columns([1.3, 1, 1])
+
+    is_clicked = col1.button(label="Generate poster!")
+    is_clicked_rerun = None
+
+    if is_clicked:
+        poster = generate_poster(data[data.title==selected_movie])
+
+    if poster is not None:
+        buffer1, col1, buffer2 = st.columns([1.3, 1, 1])
+        is_clicked_rerun = col1.button(label="Rerun with same movie!")
+
+    if is_clicked_rerun:
+        poster = generate_poster(data[data.title==selected_movie])
 
-st.title("""Movie Poster Generator""")