Update app.py

app.py

@@ -1,25 +1,26 @@
-import streamlit as st
+import gradio as gr
 from transformers import pipeline
 from PIL import Image
 
-# Gunakan model AI detector (gratis di HuggingFace)
-classifier = pipeline("image-classification", model="shuhuai/AI-image-detector")
-
-st.title("Deteksi Foto Asli vs AI Generated")
-st.write("Upload foto untuk mengecek apakah asli atau AI generated.")
-
-uploaded_file = st.file_uploader("Upload gambar", type=["jpg","jpeg","png"])
-
-if uploaded_file:
-    image = Image.open(uploaded_file)
-    st.image(image, caption="Gambar yang diupload", use_column_width=True)
-
-    result = classifier(image)
-
-    label = result[0]['label']
-    confidence = result[0]['score'] * 100
+# Gunakan model PUBLIC yang terbuka
+classifier = pipeline("image-classification", model="umm-maybe/ai-image-detector")
 
+def detect_ai(image):
+    results = classifier(image)
+    label = results[0]['label']
+    confidence = results[0]['score'] * 100
+    
     if label.lower() in ["fake", "ai-generated"]:
-        st.error(f"🚨 Kemungkinan besar **AI Generated**\n\nLabel: {label}\nConfidence: {confidence:.2f}%")
+        return f"🚨 Kemungkinan besar AI Generated\nLabel: {label}\nConfidence: {confidence:.2f}%"
     else:
-        st.success(f"✅ Kemungkinan besar **Foto Asli**\n\nLabel: {label}\nConfidence: {confidence:.2f}%")
+        return f"✅ Kemungkinan besar Foto Asli\nLabel: {label}\nConfidence: {confidence:.2f}%"
+
+demo = gr.Interface(
+    fn=detect_ai,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Deteksi Foto AI vs Asli",
+    description="Upload foto untuk mengetahui apakah ini foto asli atau hasil AI-generated."
+)
+
+demo.launch()