Update app.py

app.py

@@ -5,22 +5,25 @@ import numpy as np
 import cv2
 
 # ----------------------------
-# MODEL
+# Model AI-detector (gratis)
 # ----------------------------
 try:
-    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)
+    ai_detector = pipeline("image-classification", model="umm-maybe/AI-image-detector")
+except:
+    ai_detector = None
+    print("HF AI-detector gagal dimuat")
 
+# ----------------------------
+# Model General (backup)
+# ----------------------------
 try:
     general_model = pipeline("image-classification", model="google/vit-base-patch16-224")
-except Exception as e:
+except:
     general_model = None
-    print("General classifier gagal dimuat:", e)
+    print("General classifier gagal dimuat")
 
 # ----------------------------
-# ANALISIS LOKAL
+# Analisis kamera / lokal
 # ----------------------------
 def calculate_blur(image):
     gray = np.array(image.convert("L"))
@@ -44,28 +47,26 @@ def has_camera_exif(image):
     return False
 
 # ----------------------------
-# DETEKSI HYBRID
+# Deteksi hybrid
 # ----------------------------
 def detect_image(image):
     output_lines = []
 
-    # -------- HF AI-detector --------
-    hf_score = 0
-    hf_label = "N/A"
-    hf_conf = 0
-    if hf_detector:
+    # ---- AI-detector ----
+    ai_score = 0
+    ai_label = "N/A"
+    ai_conf = 0
+    if ai_detector:
         try:
-            result = hf_detector(image)
-            hf_label = result[0]['label']
-            hf_conf = result[0]['score'] * 100
-            if any(x in hf_label.lower() for x in ["fake", "ai", "artificial"]):
-                hf_score = hf_conf
-            elif "human" in hf_label.lower():
-                hf_score = 100 - hf_conf  # semakin besar human → kecil skor AI
+            result = ai_detector(image)
+            ai_label = result[0]['label']
+            ai_conf = result[0]['score'] * 100
+            if any(x in ai_label.lower() for x in ["fake", "ai", "artificial"]):
+                ai_score = ai_conf
         except:
-            hf_score = 0
+            ai_score = 0
 
-    # -------- General model --------
+    # ---- General model ----
     general_score = 0
     general_label = "N/A"
     general_conf = 0
@@ -74,38 +75,42 @@ def detect_image(image):
             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","3d","maya","render"]):
+            if any(x in general_label.lower() for x in ["anime","cartoon","illustration","maya","3d"]):
                 general_score = general_conf
-            else:
-                general_score = 100 - general_conf
         except:
             general_score = 0
 
-    # -------- Analisis lokal --------
+    # ---- Analisis kamera ----
     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 += 50
-    if not exif_present:
-        local_score += 10
+    camera_score = 0
+    if blur_score > 100:  # Foto asli biasanya lebih fokus
+        camera_score += 40
+    if noise_score > 15:  # Sensor noise alami
+        camera_score += 30
+    if exif_present:      # Ada EXIF
+        camera_score += 30
 
-    # -------- Weighted Score --------
-    weighted_score = hf_score*0.6 + general_score*0.2 + local_score*0.2
-    weighted_score = min(max(weighted_score, 0), 100)  # pastikan 0–100
+    # ---- Weighted hybrid score ----
+    weighted_ai = ai_score * 0.6 + general_score * 0.2
+    weighted_camera = camera_score
+    final_score = weighted_camera - weighted_ai  # Positif = asli, Negatif = AI
 
-    # -------- Output Final --------
-    if weighted_score >= 95:
-        final_result = "🤖 Gambar ini hasil AI"
-    elif weighted_score <= 5:
+    if final_score >= 95:
         final_result = "✅ Gambar ini asli"
+    elif final_score <= -95:
+        final_result = "🤖 Gambar ini hasil AI"
     else:
-        final_result = f"⚖️ Gambar ini {weighted_score:.2f}% AI, {100-weighted_score:.2f}% asli"
+        # Persentase
+        if final_score > 0:
+            final_result = f"✅ Gambar ini {min(round(final_score,2),100)}% asli"
+        else:
+            final_result = f"🤖 Gambar ini {min(round(-final_score,2),100)}% hasil AI"
 
+    # ---- Output ----
     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"AI-detector: {ai_label} ({ai_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}")
@@ -121,7 +126,7 @@ iface = gr.Interface(
     inputs=gr.Image(type="pil"),
     outputs="markdown",
     title="AI vs Foto Asli Detector (Hybrid)",
-    description="Unggah gambar, sistem akan mendeteksi persentase AI vs asli. 100% AI → hasil AI, 100% asli → asli."
+    description="Unggah gambar, sistem akan mendeteksi apakah gambar asli atau hasil AI (menggunakan kombinasi AI-detector dan jejak kamera)."
 )
 
 if __name__ == "__main__":