Upload 2 files

app.py

@@ -8,23 +8,21 @@ 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 sentence_transformers import SentenceTransformer
-from diffusers import DiffusionPipeline
 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 ---- ##
 ###############################
 
 
-IS_MODEL_LOADED = False
 PATH_JSON = '/home/user/.kaggle/kaggle.json'
 
 
@@ -123,14 +121,6 @@ def authenticate_kaggle():
     api = KaggleApi()
     api.authenticate()
 
-    '''
-    try:
-        api.authenticate()
-    except:
-        with open(PATH_JSON, 'w') as file:
-            json.dump(api_token, file)
-        api.authenticate()
-    '''
 
 @st.experimental_memo(persist=True, show_spinner=False, suppress_st_warning=True)
 def load_dataset():
@@ -166,14 +156,6 @@ def load_dataset():
 
     return data
 
-@st.cache(persist=True, show_spinner=False, allow_output_mutation=True, suppress_st_warning=True)
-def load_model():
-    model = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
-    IS_MODEL_LOADED = True
-    return model
-    #return DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
-    #return DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-2")
-
 
 def query_summary(text):
     """
@@ -226,18 +208,16 @@ def generate_poster(movie_data):
 
 
     # Get image based on synopsis
-    with st.spinner("Generating poster image...\nThis may take some time, please be patient"):
+    with st.spinner("Generating poster image..."):
         poster_image = query_generate(synopsis_sum)
 
-    import io
-    from PIL import Image
+    # Show image
     try: 
         image = Image.open(io.BytesIO(poster_image))
-        st.image(image, caption=movie_data.title.values[0])
-        return image
+        st.image(image, caption="Movie: " + movie_data.title.values[0])
     except:
         st.text(poster_image)
-        return poster_image
+
 
     return image
 # ------------------------------------------------------- #
@@ -288,11 +268,5 @@ if __name__ == "__main__":
 
 
     if is_clicked:
-        image = generate_poster(data[data.title==session.selected_movie])
-
-    st.text("")
-    st.text("")
-    st.text("")
+        generate_poster(data[data.title==session.selected_movie])
 
-    if image is not None:
-        st.image(image, caption=session.selected_movie.title.values[0])

requirements.txt

@@ -4,4 +4,5 @@ zipfile39
 sentence-transformers
 diffusers
 accelerate
-htbuilder
+htbuilder
+PIL