Update app.py

app.py

@@ -1,31 +1,53 @@
 import gradio as gr
 from transformers import pipeline
-from PIL import Image
 
-# Model deteksi AI vs Asli (tanpa moondream2, biar tidak error trust_remote_code)
+# Daftar model publik yang relatif stabil
 model_ids = [
     "umm-maybe/AI-image-detector",
-    "roberta-base-openai-detector"
+    "falconsai/nsfw_image_detection",   # meski nsfw, output-nya bermanfaat untuk fitur visual
+    "microsoft/resnet-50"               # model general untuk referensi real-world image
 ]
 
+# Load semua model
 detectors = [pipeline("image-classification", model=m) for m in model_ids]
 
 def detect_image(image):
-    results = []
-    for det in detectors:
-        preds = det(image)
-        if isinstance(preds, list) and len(preds) > 0:
-            label = preds[0]["label"]
-            score = preds[0]["score"]
-            results.append(f"{label}: {score:.2f}")
-    return "\n".join(results)
+    combined_scores = {}
+    results_text = []
 
+    # Jalankan semua model
+    for i, detector in enumerate(detectors):
+        preds = detector(image)
+        results_text.append(f"Model {i+1} ({model_ids[i]}):")
+        for p in preds:
+            label = p["label"]
+            score = float(p["score"])
+            results_text.append(f"  {label}: {round(score*100, 2)}%")
+
+            # Gabungkan skor
+            if label not in combined_scores:
+                combined_scores[label] = []
+            combined_scores[label].append(score)
+
+    # Hitung rata-rata dari semua model
+    final_scores = {label: sum(scores)/len(scores) for label, scores in combined_scores.items()}
+
+    # Cari label dengan skor tertinggi
+    best_label = max(final_scores, key=final_scores.get)
+    best_score = round(final_scores[best_label]*100, 2)
+
+    results_text.append("\n=== ENSEMBLE HASIL AKHIR ===")
+    results_text.append(f"{best_label} ({best_score}%)")
+
+    return "\n".join(results_text)
+
+# Gradio interface
 iface = gr.Interface(
     fn=detect_image,
     inputs=gr.Image(type="pil"),
     outputs="text",
-    title="AI vs Real Image Detector",
-    description="Upload a photo to check if it's AI-generated or a real one using multiple models."
+    title="AI vs Real Image Detector (3-Model Ensemble)",
+    description="Menggabungkan 3 model publik untuk meningkatkan akurasi deteksi gambar AI vs asli."
 )
 
 if __name__ == "__main__":