Update app.py

app.py

@@ -1,74 +1,52 @@
-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")
-
-# Bobot tiap model
-weights = {
-    "prithivMLmods": 1.2,
-    "dima806": 1.0,
-    "Hemg": 1.5
-}
-
 def detect_image(img: Image.Image):
     results = {}
 
-    # Run semua model
+    # Model 1
     res1 = model1(img)
-    res2 = model2(img)
-    res3 = model3(img)
     results["Model 1 (prithivMLmods)"] = res1
+
+    # Model 2
+    res2 = model2(img)
     results["Model 2 (dima806)"] = res2
+
+    # Model 3
+    res3 = model3(img)
     results["Model 3 (Hemg)"] = res3
 
-    # Ensemble dengan bobot
+    # --- Ensemble dengan aturan baru ---
     ai_score, real_score = 0, 0
-    for name, res in zip(["prithivMLmods", "dima806", "Hemg"], [res1, res2, res3]):
+    real_votes, ai_votes = 0, 0
+
+    for res in [res1, res2, res3]:
         top = res[0]
         label = top["label"].lower()
-        score = top["score"] * weights[name]
+        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
+    # Normalisasi skor
     total = ai_score + real_score + 1e-9
     ai_percent = (ai_score / total) * 100
     real_percent = (real_score / total) * 100
 
-    # Threshold khusus: jika ada model dengan real_score > 0.6 → override jadi real
-    override_real = any(
-        any("real" in r["label"].lower() and r["score"] > 0.6 for r in res)
-        for res in [res1, res2, res3]
-    )
-
-    if override_real or real_percent > ai_percent:
+    # Keputusan akhir (butuh ≥2 real votes)
+    if real_votes >= 2:
         verdict = f"✅ Foto Asli ({real_percent:.2f}%)"
     else:
         verdict = f"⚠️ AI Generated ({ai_percent:.2f}%)"
 
     # Format output
-    output = "## 📊 Ringkasan Deteksi\n"
+    output = f"## 📊 Ringkasan Deteksi\n"
     for name, res in results.items():
         output += f"\n🔹 **{name}**: {res}\n"
 
     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 voting berbobot & threshold untuk deteksi AI vs real."
-)
-
-if __name__ == "__main__":
-    iface.launch()