Update app.py

app.py

@@ -1,32 +1,46 @@
-import gradio as gr
 from transformers import pipeline
-from PIL import Image
+import gradio as gr
+from PIL import Image, ExifTags
 
-# Gunakan model deteksi publik
-classifier = pipeline("image-classification", model="dima806/deepfake_vs_real_image_detection")
+# Muat model Hugging Face khusus deteksi AI
+classifier = pipeline("image-classification", model="elacour/ai-image-detection")
+
+def detect_image(image):
+    # --- Cek metadata (EXIF) ---
+    exif = {}
+    try:
+        raw_exif = image._getexif()
+        if raw_exif:
+            exif = {ExifTags.TAGS.get(k, k): v for k, v in raw_exif.items()}
+    except:
+        pass
+    
+    if not exif:
+        exif_result = "⚠️ Tidak ada metadata kamera → kemungkinan besar AI atau editan"
+    else:
+        exif_result = "✅ Metadata kamera terdeteksi"
 
-def detect(image):
-    # image dari Gradio
+    # --- Prediksi model ---
     results = classifier(image)
-    # hasil tertinggi
-    best = max(results, key=lambda x: x['score'])
-    label = best['label']
-    confidence = best['score'] * 100
+    label = results[0]["label"]
+    score = results[0]["score"] * 100
 
-    if "fake" in label.lower() or "generated" in label.lower() or "ai" in label.lower():
-        verdict = "⚠️ Kemungkinan besar Gambar AI / Fake"
+    if "fake" in label.lower() or "ai" in label.lower():
+        verdict = "🚨 Kemungkinan besar Hasil AI"
     else:
-        verdict = "✅ Kemungkinan besar Foto Asli"
+        verdict = "📷 Kemungkinan besar Foto Asli"
 
-    return f"{verdict}\n\nLabel: {label}\nConfidence: {confidence:.2f}%"
+    # --- Gabungan hasil ---
+    final_result = f"{verdict}\n\nLabel Model: {label}\nConfidence: {score:.2f}%\n\nCek Metadata: {exif_result}"
+    return final_result
 
-app = gr.Interface(
-    fn=detect,
-    inputs=gr.Image(type="pil", label="Upload Foto"),
-    outputs=gr.Textbox(label="Hasil Deteksi"),
-    title="Detektor Foto vs AI",
-    description="Unggah foto realistik untuk mendeteksi apakah foto asli atau hasil AI."
+# Buat UI Gradio
+iface = gr.Interface(
+    fn=detect_image,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Hybrid AI Image Detector",
+    description="Upload foto untuk mendeteksi apakah gambar hasil kamera asli atau hasil AI."
 )
 
-if __name__ == "__main__":
-    app.launch()
+iface.launch()