Update app.py

app.py

@@ -26,7 +26,7 @@ ALLOWED_EXT = {"png", "jpg", "jpeg", "webp"}
 ROOT_DIR = "." 
 MODEL_FILES = ["ckpt_best_v4_epoch8.pth", "ckpt_best_v4_epoch14.pth"]
 
-# Threshold murni hasil optimasi batas overlap data pengujian Anda
+# Threshold murni untuk filter internal model Deep Learning
 MODEL_THRESHOLD = 0.615
 
 # ==========================================
@@ -95,14 +95,15 @@ def startup_event():
         raise RuntimeError(f"Startup digagalkan server: {e}")
 
 # ==========================================
-# 🔬 LAB FORENSIK DIGITAL - PURE EMSEMBLE ENGINE
+# 🔬 LAB FORENSIK DIGITAL - WITH WHATSAPP BYPASS
 # ==========================================
 def run_full_forensic_pipeline(img_pil: Image.Image, img_cv, file_bytes, filename):
     img_gray = cv2.cvtColor(img_cv, cv2.COLOR_BGR2GRAY)
     h, w, c = img_cv.shape
     
-    # Penghitung indikator palsu biner (Hanya dipertahankan untuk info sekunder JSON)
+    # Inisialisasi Poin Penalti untuk Penggabungan Keputusan
     poin_penalti_fake = 0
+    total_aturan = 5
     
     # Deteksi Otomatis Jalur Kompresi WhatsApp via Nama Berkas
     fname_lower = filename.lower()
@@ -117,6 +118,7 @@ def run_full_forensic_pipeline(img_pil: Image.Image, img_cv, file_bytes, filenam
     exif = img_pil._getexif()
     step1 = "Ada metadata EXIF (Kamera Asli)" if exif else "Metadata kosong (Khas Gambar AI/Screenshot)"
     if not exif and not is_whatsapp:
+        # Penalti dinonaktifkan untuk WhatsApp karena kompresi sistem WA pasti menghapus EXIF
         poin_penalti_fake += 1  
     
     # [Step 2/12] Analisis Pixel (Komite Binary + TTA)
@@ -131,17 +133,19 @@ def run_full_forensic_pipeline(img_pil: Image.Image, img_cv, file_bytes, filenam
         preds14 = F.softmax(models_ensemble[1](batch_t), dim=1).cpu().numpy()
         probs_epoch14 = np.mean(preds14, axis=0)
     
-    # Perhitungan bobot kombinasi biner untuk kelas FAKE (indeks 1)
     prob_fake_raw = float((0.4 * probs_epoch8[1]) + (0.6 * probs_epoch14[1]))
     step2 = f"Score Indikasi AI: {prob_fake_raw * 100:.1f}%"
     
-    if prob_fake_raw >= MODEL_THRESHOLD:
+    # Aturan Khusus WhatsApp: Naikkan batas threshold model AI agar tidak sensitif pada noise rusak WA
+    THRESHOLD_MODEL_ACTUAL = 0.85 if is_whatsapp else MODEL_THRESHOLD
+    if prob_fake_raw >= THRESHOLD_MODEL_ACTUAL:
         poin_penalti_fake += 1  
     
     # [Step 3/12] Analisis Pola Sensor CFA
     diff_cfa = np.mean(np.abs(img_gray[1:, :] - img_gray[:-1, :]))
     step3 = "Pola interpolasi mulus alami" if diff_cfa < 15.0 else "Anomali interpolasi piksel buatan terdeteksi"
     if diff_cfa >= 15.0 and not is_whatsapp:
+        # Penalti dinonaktifkan untuk WhatsApp karena kompresi WA merusak interpolasi alami piksel sensor
         poin_penalti_fake += 1  
     
     # [Step 4/12] Pencarian jejak Hex/Binary
@@ -197,15 +201,14 @@ def run_full_forensic_pipeline(img_pil: Image.Image, img_cv, file_bytes, filenam
         poin_penalti_fake += 1  
     
     # =======================================================
-    # ⚖️ KEPUTUSAN MURNI MATEMATIKA MODEL ENSEMBLE (SAY NO TO 60%)
+    # KETOK PALU KEPUTUSAN GABUNGAN MATEMATIKA MULTI-EVIDENCE
     # =======================================================
-    # Mengembalikan kendali penuh tingkat keakuratan ke persenan halus model
-    if prob_fake_raw >= MODEL_THRESHOLD:
-        prediction = "AI"
-        confidence = prob_fake_raw * 100
+    if poin_penalti_fake >= 3:
+        prediction = "AI"  # Menyesuaikan label tampilan sistem frontend web Anda ("AI" / "REAL")
+        confidence = (poin_penalti_fake / total_aturan) * 100
     else:
         prediction = "REAL"
-        confidence = (1.0 - prob_fake_raw) * 100
+        confidence = ((total_aturan - poin_penalti_fake) / total_aturan) * 100
 
     forensic_logs = {
         "step_1": f"[Step 1/12] Metadata: {step1}",
@@ -231,9 +234,9 @@ def run_full_forensic_pipeline(img_pil: Image.Image, img_cv, file_bytes, filenam
 def root():
     return {
         "status": "online",
-        "engine": "Pure Ensemble Deep Learning Engine (Fine Confidence)",
+        "engine": "Hybrid Integrated Forensic Engine (WhatsApp Bypass Fixed)",
         "models_loaded": len(models_ensemble) == 2,
-        "model_threshold": f"{MODEL_THRESHOLD * 100}%"
+        "hybrid_voting_rules_count": 5
     }
 
 @app.post("/predict")
@@ -257,22 +260,22 @@ async def predict(file: UploadFile = File(...)):
         if img_cv is None:
             raise ValueError("File korup atau struktur piksel tidak valid")
 
-        # Eksekusi pipeline murni
+        # Eksekusi pipeline terintegrasi baru dengan parameter operan filename
         prediction, confidence, raw_score, forensic_steps, is_monochrome, active_penalties = run_full_forensic_pipeline(
             img_pil, img_cv, file_bytes, filename
         )
 
         return {
             "filename": filename,
-            "prediction": prediction,                  # "REAL" atau "AI" murni komite binary
-            "confidence": f"{confidence}%",             # Nilai persenan halus (misal: 95.5%, 81.3%)
-            "raw_deep_learning_score": f"{raw_score}%", # Skor murni kelas FAKE
+            "prediction": prediction,
+            "confidence": f"{confidence}%",
+            "raw_deep_learning_score": f"{raw_score}%",
             "active_fake_indicators": f"{active_penalties} dari 5",
-            "is_monochrome_detected": is_monochrome,    # Trigger Warning Banner jika gambar hitam-putih
-            "forensic_analysis_logs": forensic_steps    # Log 12 langkah lengkap untuk drop-down UI
+            "is_monochrome_detected": is_monochrome,
+            "forensic_analysis_logs": forensic_steps
         }
     except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Gagal memproses analisis forensik: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Gagal memproses analisis gabungan forensik: {str(e)}")
 
 @app.post("/save-feedback")
 async def save_feedback(file: UploadFile = File(...), correct_label: str = Form(...)):