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app.py

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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
+
+from streamlit import session_state as session
+from datetime import time, datetime
+from zipfile import ZipFile
+from kaggle.api.kaggle_api_extended import KaggleApi
+from sentence_transformers import SentenceTransformer
+from diffusers import DiffusionPipeline
+
+
+###############################
+## ------- FUNCTIONS ------- ##
+###############################
+
+#@st.cache(persist=True, show_spinner=False, suppress_st_warning=True)
+@st.experimental_memo(persist=True, show_spinner=False, suppress_st_warning=True)
+def load_dataset():
+    """
+    Load Dataset from Kaggle
+    -return: dataframe containing dataset
+    """
+    # 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
+
+@st.cache
+def load_model():
+    #return DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+    return DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
+
+
+def query_summarization(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()
+    return response[0].get('summary_text')
+
+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_summarization(movie_data.overview.values[0])
+    st.text(synopsis_sum)
+
+    # Get image based on synopsis
+    pipeline = load_model()
+    #pipeline = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-2")
+
+    #image = pipe(prompt).images[0]
+    #st.image(image, caption=movie_data.title)
+
+    return None #poster_image
+
+
+###############################
+## --- CONNECT TO KAGGLE --- ##
+###############################
+
+# Authenticate Kaggle account
+os.environ['KAGGLE_USERNAME'] = st.secrets['username']
+os.environ['KAGGLE_KEY'] = st.secrets['key']
+
+
+api_token = {"username":st.secrets['username'],"key":st.secrets['key']}
+with open('/home/appuser/.kaggle/kaggle.json', 'w') as file:
+    json.dump(api_token, file)
+
+
+# Activate Kaggle API
+
+try:
+    api = KaggleApi()
+    api.authenticate()
+except:
+    with open('/home/appuser/.kaggle/kaggle.json', 'w') as file:
+        json.dump(api_token, file)
+    api = KaggleApi()
+    api.authenticate() 
+
+
+
+###############################
+## --------- MAIN ---------- ##
+###############################
+
+image = None
+
+# Create dataset
+data = load_dataset()
+
+
+st.title("""
+Alternative 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.
+ """)
+
+st.text("")
+st.text("")
+st.text("")
+st.text("")
+
+session.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!")
+
+
+if is_clicked:
+    image = generate_poster(data[data.title==session.selected_movie])
+
+st.text("")
+st.text("")
+st.text("")
+st.text("")
+
+#if data is not None:
+#    st.table(data)

requirements.txt

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+
+kaggle
+zipfile39
+sentence-transformers
+diffusers
+accelerate