Update app.py

app.py

@@ -1,14 +1,13 @@
 # import part
 import streamlit as st
 from transformers import pipeline
-
+import torch
 
 # function part
 # img2text
-def img2text(img):
-    image_to_text_model = pipeline("image-to-text", 
-                                   model="Salesforce/blip-image-captioning-base")
-    text = image_to_text_model(img)[0]["generated_text"]
+def img2text(url):
+    image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
+    text = image_to_text_model(url)[0]["generated_text"]
     return text
 
 # text2story
@@ -29,13 +28,15 @@ def text2audio(story_text):
 st.set_page_config(page_title="Your Image to Audio Story",
                    page_icon="🦜")
 st.header("Turn Your Image to Audio Story")
-uploaded_file = st.file_uploader("Select an Image...", type=["jpg", "jpeg", "png"])
+uploaded_file = st.file_uploader("Select an Image..."）#, type=["jpg", "jpeg", "png"])
 
 
 if uploaded_file is not None:
-    print(uploaded_file)
-    st.image(uploaded_file, caption="Uploaded Image",
-             use_column_width=True)  
+        print(uploaded_file)
+        bytes_data = uploaded_file.getvalue()
+        with open(uploaded_file.name, "wb") as file:
+            file.write(bytes_data)
+        st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
     
 
     #Stage 1: Image to Text