Update app.py

app.py

@@ -1,6 +1,5 @@
 import streamlit as st
 import requests
-from io import BytesIO
 
 # Hugging Face Inference API URL and Token
 API_URL = "https://api-inference.huggingface.co/models/Organika/sdxl-detector"
@@ -8,6 +7,7 @@ API_TOKEN = st.secrets["HF_API_TOKEN"]  # You'll store this in the Hugging Face
 
 headers = {"Authorization": f"Bearer {API_TOKEN}"}
 
+# Function to query the model
 def query(image_bytes):
     response = requests.post(API_URL, headers=headers, files={"inputs": image_bytes})
     return response.json()
@@ -17,17 +17,17 @@ st.title("AI Image Detector")
 
 st.write("Upload an image, and we will check if it is AI-generated using the Hugging Face SDXL detector.")
 
+# File uploader for user to upload image
 uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 
 if uploaded_file is not None:
     # Display the uploaded image
-    image = uploaded_file.read()
-    st.image(image, caption="Uploaded Image", use_column_width=True)
+    st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
     
     st.write("Classifying...")
     
     # Send the image to the model
-    result = query(image)
+    result = query(uploaded_file)  # Use the file object directly
     
     # Display the result
     if "error" in result: