Update app.py

app.py

@@ -2,32 +2,36 @@ import gradio as gr
 from transformers import pipeline
 from PIL import Image
 
-# === Load 3 model publik khusus AI vs Real ===
+# 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 = {}
 
-    # Model 1
+    # Run semua model
     res1 = model1(img)
-    results["Model 1 (prithivMLmods)"] = res1
-
-    # Model 2
     res2 = model2(img)
-    results["Model 2 (dima806)"] = res2
-
-    # Model 3
     res3 = model3(img)
+    results["Model 1 (prithivMLmods)"] = res1
+    results["Model 2 (dima806)"] = res2
     results["Model 3 (Hemg)"] = res3
 
-    # --- Ensemble sederhana ---
+    # Ensemble dengan bobot
     ai_score, real_score = 0, 0
-    for res in [res1, res2, res3]:
+    for name, res in zip(["prithivMLmods", "dima806", "Hemg"], [res1, res2, res3]):
         top = res[0]
         label = top["label"].lower()
-        score = top["score"]
+        score = top["score"] * weights[name]
+
         if "real" in label:
             real_score += score
         else:
@@ -38,14 +42,19 @@ def detect_image(img: Image.Image):
     ai_percent = (ai_score / total) * 100
     real_percent = (real_score / total) * 100
 
-    # Keputusan akhir
-    if real_percent > ai_percent:
+    # 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:
         verdict = f"✅ Foto Asli ({real_percent:.2f}%)"
     else:
         verdict = f"⚠️ AI Generated ({ai_percent:.2f}%)"
 
     # Format output
-    output = f"## 📊 Ringkasan Deteksi\n"
+    output = "## 📊 Ringkasan Deteksi\n"
     for name, res in results.items():
         output += f"\n🔹 **{name}**: {res}\n"
 
@@ -58,7 +67,7 @@ iface = gr.Interface(
     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) untuk mendeteksi apakah gambar AI-generated atau asli."
+    description="Menggunakan 3 model publik Hugging Face (prithivMLmods, dima806, Hemg) dengan voting berbobot & threshold untuk deteksi AI vs real."
 )
 
 if __name__ == "__main__":