Update app.py

app.py

@@ -1,25 +1,33 @@
-import requests
 import streamlit as st
-import base64
+import requests
 
+# Define the API endpoint
+API_ENDPOINT = "https://ashrafb-salesforce-blip-image-captioning-base.hf.space/run/predict"
+
+# Define the Streamlit app
 def main():
-    st.title("Hugging Face Spaces Image Captioning App")
+    st.title("Image Captioning App")
     
-    uploaded_image = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
-
-    if uploaded_image is not None:
-        # Read the uploaded image and convert it to base64
-        image_content = uploaded_image.read()
-        encoded_image = base64.b64encode(image_content).decode()
-
-        # Make a request to the Hugging Face Spaces API
-        response = requests.post("https://ashrafb-salesforce-blip-image-captioning-base.hf.space/run/predict", json={
-            "data": ["data:image/png;base64," + encoded_image]
-        }).json()
-
-        # Display the caption
-        caption = response["data"][0]
-        st.image(image_content, caption=caption, use_column_width=True)
+    # Upload image
+    uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
+    
+    if uploaded_file is not None:
+        # Display the uploaded image
+        st.image(uploaded_file, caption="Uploaded Image.", use_column_width=True)
+        
+        # Prepare the data for the API request
+        image_data = uploaded_file.read()
+        image_base64 = b64encode(image_data).decode('utf-8')
+        payload = {"data": ["data:image/jpeg;base64," + image_base64]}
+        
+        # Make the API request
+        response = requests.post(API_ENDPOINT, json=payload).json()
+        
+        # Display the caption from the API response
+        caption = response["data"][0]["captions"][0]["caption"]
+        st.subheader("Generated Caption:")
+        st.write(caption)
 
+# Run the app
 if __name__ == "__main__":
     main()