Update app.py

app.py

@@ -1,6 +1,6 @@
 import streamlit as st
 from transformers import pipeline
-from diffusers import DiffusionPipeline
+#from diffusers import DiffusionPipeline
 from PIL import Image
 import requests
 import io
@@ -9,7 +9,7 @@ import io
 image_to_text = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
 
 # Load the text-to-image model
-text_to_image = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0")
+#text_to_image = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0")
 
 def main():
     st.title("Image to Story to Image Converter")
@@ -21,22 +21,26 @@ def main():
     if input_option == "Text":
         text_input = st.text_input("Enter the text:")
         if st.button("Generate Story and Image") and text_input:
-            generate_image(text_input)
+            #generate_image(text_input)
+            st.success(f'Generated Caption: {text_input}')
+            
 
     # Input URL
     elif input_option == "URL":
-        uploaded_file = st.file_uploader("Upload an image file:", type=["jpg", "jpeg", "png"])
-        if uploaded_file is not None:
-            image = Image.open(uploaded_file)
-            st.image(image, caption="Uploaded Image", use_column_width=True)
-            if st.button("Generate Story and Image"):
-                image_text = image_to_text_from_file(uploaded_file)
-                generate_image(image_text)
-        else:
-            image_url = st.text_input("Enter the image URL:")
-            if st.button("Generate Story and Image") and image_url:
-                image_text = image_to_text_from_url(image_url)
-                generate_image(image_text)
+        #uploaded_file = st.file_uploader("Upload an image file:", type=["jpg", "jpeg", "png"])
+        #if uploaded_file is not None:
+            #image = Image.open(uploaded_file)
+            #st.image(image, caption="Uploaded Image", use_column_width=True)
+            #if st.button("Generate Story and Image"):
+                #image_text = image_to_text_from_file(uploaded_file)
+                #generate_image(image_text)
+        #else:
+        image_url = st.text_input("Enter the image URL:")
+        if st.button("Generate Story and Image") and image_url:
+            image_text = image_to_text_from_url(image_url)
+            #generate_image(image_text)
+            st.success(f'Generated Caption: {image_text}')
+            
 
 def image_to_text_from_file(uploaded_file):
     image_bytes = io.BytesIO(uploaded_file.read())