Update app.py

app.py

@@ -8,11 +8,17 @@ import cv2
 # MODEL DETEKSI AI
 # ----------------------------
 try:
-    hf_detector = pipeline("image-classification", model="ckpt/real-or-ai")  # model gratis HF khusus AI detection
+    hf_detector = pipeline("image-classification", model="umm-maybe/AI-image-detector")
 except Exception as e:
     hf_detector = None
     print("HF AI-detector gagal dimuat:", e)
 
+try:
+    general_model = pipeline("image-classification", model="google/vit-base-patch16-224")
+except Exception as e:
+    general_model = None
+    print("General classifier gagal dimuat:", e)
+
 # ----------------------------
 # ANALISIS LOKAL
 # ----------------------------
@@ -38,11 +44,12 @@ def has_camera_exif(image):
     return False
 
 # ----------------------------
-# DETEKSI HYBRID
+# DETEKSI HYBRID DENGAN THRESHOLD LAMA
 # ----------------------------
 def detect_image(image: Image.Image):
     output_lines = []
 
+    # -------- HF AI-detector --------
     hf_score = 0
     hf_label = "N/A"
     hf_conf = 0
@@ -51,32 +58,46 @@ def detect_image(image: Image.Image):
             result = hf_detector(image)
             hf_label = result[0]['label']
             hf_conf = result[0]['score'] * 100
-            if "ai" in hf_label.lower() or "synthetic" in hf_label.lower():
+            if any(x in hf_label.lower() for x in ["fake", "ai", "artificial"]):
                 hf_score = hf_conf
         except:
             hf_score = 0
 
-    # Threshold HF lebih rendah agar sensitif
-    if hf_score > 30:
+    if hf_score > 50:  # threshold HF lama
         final_result = "🤖 AI Detected"
         weighted_score = hf_score
         output_lines.append(f"### Hasil Deteksi:\n{final_result}")
         output_lines.append(f"HF AI-detector: {hf_label} ({hf_conf:.2f}%)")
         return "\n".join(output_lines)
 
-    # Analisis lokal tambahan
+    # -------- General model --------
+    general_score = 0
+    general_label = "N/A"
+    general_conf = 0
+    if general_model:
+        try:
+            result2 = general_model(image)
+            general_label = result2[0]['label']
+            general_conf = result2[0]['score'] * 100
+            if any(x in general_label.lower() for x in ["anime","cartoon","illustration","maya","3d"]):
+                general_score = general_conf
+        except:
+            general_score = 0
+
+    # -------- Analisis lokal --------
     blur_score = calculate_blur(image)
     noise_score = calculate_noise(image)
     exif_present = has_camera_exif(image)
     local_score = 0
     if blur_score < 100 or noise_score < 10:
-        local_score += 30
+        local_score += 50
     if not exif_present:
-        local_score += 20
+        local_score += 10
 
-    weighted_score = hf_score * 0.6 + local_score * 0.4
+    # -------- Weighted Score --------
+    weighted_score = general_score*0.7 + local_score*0.3
 
-    if weighted_score > 40:
+    if weighted_score > 50:
         final_result = "🤖 AI Detected"
     else:
         final_result = "✅ Foto Asli"
@@ -85,6 +106,7 @@ def detect_image(image: Image.Image):
     output_lines.append(f"### Hasil Deteksi:\n{final_result}")
     output_lines.append(f"Weighted Skor: {weighted_score:.2f}")
     output_lines.append(f"HF AI-detector: {hf_label} ({hf_conf:.2f}%)")
+    output_lines.append(f"General Model: {general_label} ({general_conf:.2f}%)")
     output_lines.append(f"Blur Score: {blur_score:.2f}")
     output_lines.append(f"Noise Score: {noise_score:.2f}")
     output_lines.append(f"Metadata Kamera: {'Ada' if exif_present else 'Tidak Ada'}")