Update app.py

app.py

@@ -10,22 +10,33 @@ pipe = pipeline('image-classification', model=model_name)
 st.title("Deepfake vs Real Image Detection")
 
 uploaded_file = st.file_uploader("Choose an image...", type="jpg")
+
 if uploaded_file is not None:
-    image = Image.open(uploaded_file)
-    st.image(image, caption='Uploaded Image.', use_column_width=True)
-    st.write("")
-    st.write("Classifying...")
+   image = Image.open(uploaded_file)
+   st.image(image, caption='Uploaded Image.', use_column_width=True)
+
+   st.write("")
+   st.write("Classifying...")
 
-    # Apply the model
-    result = pipe(image)
+   # Apply the model
+   result = pipe(image)
 
-    # Display the result
-    st.write("Classification Result:")
-    st.write("---------------")
+   # Display the result
+   st.write("**Classification Result:**")
+   st.write("---------------")
+   for i, res in enumerate(result):
+       label = res["label"]
+       score = res["score"] * 100  # Convert to percentage
+       st.write(f"**{i+1}. {label}**: {score:.2f}%")
+   st.write("---------------")
 
-    for i, res in enumerate(result):
-        label = res["label"]
-        score = res["score"]
-        st.write(f"**{i+1}. {label}**: {score:.2f}%")
+   # Determine the majority score
+   real_score = result[0]["score"] * 100
+   fake_score = result[1]["score"] * 100
+   if real_score > fake_score:
+       majority_label = "Real"
+   else:
+       majority_label = "Fake"
 
-    st.write("---------------")
+   # Display the final result
+   st.write(f"**Given image is {majority_label}**")