Update app.py

app.py

@@ -1,3 +1,12 @@
+import gradio as gr
+from transformers import pipeline
+from PIL import Image
+
+# === Load 3 model publik khusus AI vs Real ===
+model1 = pipeline("image-classification", model="prithivMLmods/AI-vs-Deepfake-vs-Real")
+model2 = pipeline("image-classification", model="dima806/ai_vs_real_image_detection")
+model3 = pipeline("image-classification", model="Hemg/AI-VS-REAL-IMAGE-DETECTION")
+
 def detect_image(img: Image.Image):
     results = {}
 
@@ -13,34 +22,29 @@ def detect_image(img: Image.Image):
     res3 = model3(img)
     results["Model 3 (Hemg)"] = res3
 
-    # --- Ensemble dengan aturan baru ---
+    # --- Ensemble dengan threshold agar lebih stabil ---
     ai_score, real_score = 0, 0
-    real_votes, ai_votes = 0, 0
-
     for res in [res1, res2, res3]:
-        top = res[0]
-        label = top["label"].lower()
-        score = top["score"]
-
-        if "real" in label:
-            real_score += score
-            if score >= 0.5:  # ambang confidence
-                real_votes += 1
-        else:
-            ai_score += score
-            if score >= 0.5:
-                ai_votes += 1
-
-    # Normalisasi skor
+        for item in res:
+            label = item["label"].lower()
+            score = item["score"]
+            if "real" in label:
+                real_score += score
+            elif "fake" in label or "deepfake" in label or "artificial" in label:
+                ai_score += score
+
+    # Normalisasi
     total = ai_score + real_score + 1e-9
     ai_percent = (ai_score / total) * 100
     real_percent = (real_score / total) * 100
 
-    # Keputusan akhir (butuh ≥2 real votes)
-    if real_votes >= 2:
+    # Keputusan akhir dengan threshold
+    if real_percent > ai_percent and real_percent > 55:  
         verdict = f"✅ Foto Asli ({real_percent:.2f}%)"
-    else:
+    elif ai_percent > real_percent and ai_percent > 55:
         verdict = f"⚠️ AI Generated ({ai_percent:.2f}%)"
+    else:
+        verdict = f"⚠️ Tidak Pasti (Real {real_percent:.2f}%, AI {ai_percent:.2f}%)"
 
     # Format output
     output = f"## 📊 Ringkasan Deteksi\n"
@@ -50,3 +54,14 @@ def detect_image(img: Image.Image):
     output += f"\n=== 🧠 ENSEMBLE HASIL AKHIR ===\n{verdict}\n"
 
     return output
+
+iface = gr.Interface(
+    fn=detect_image,
+    inputs=gr.Image(type="pil"),
+    outputs="markdown",
+    title="Deteksi AI vs Foto Asli (Ensemble 3 Model Publik)",
+    description="Menggunakan 3 model publik Hugging Face (prithivMLmods, dima806, Hemg) dengan threshold untuk mendeteksi apakah gambar AI-generated atau asli."
+)
+
+if __name__ == "__main__":
+    iface.launch()