Update app.py

app.py

@@ -52,7 +52,7 @@ def normalize_ocr(recs):
 def format_plate(s: str) -> str:
     """‘DD AAA DDDD’  veya Unknown"""
     s = re.sub(r'[^A-Z0-9]', '', s.upper())
-    m = re.match(r'^(\d{2})([A-Z]{1,3})(\d{2,4})$', s)
+    m = re.match(r'^(\d{2})([A-Z]{1,3})([A-Z0-9]{2,4})$', s)
     return f"{m.group(1)} {m.group(2)} {m.group(3)}" if m else "Unknown"
 
 # ─── 5) Single-image inference
@@ -62,9 +62,17 @@ def run_image(img, conf=0.25):
     res = yolo(bgr, conf=conf)[0]
     out = bgr.copy()
 
-    for box in res.boxes.xyxy.cpu().numpy().astype(int):
-        x1,y1,x2,y2 = box
+    # YOLO’dan gelen tüm kutuları al
+    boxes = res.boxes.xyxy.cpu().numpy().astype(int)
+    if len(boxes):
+        # genişlik*yükseklik’e göre en büyüğü seç
+        w = boxes[:,2] - boxes[:,0]
+        h = boxes[:,3] - boxes[:,1]
+        idx = int(np.argmax(w * h))
+        x1,y1,x2,y2 = boxes[idx]
         crop = out[y1:y2, x1:x2]
+    
+
         if crop.size == 0:
             continue
 
@@ -103,9 +111,16 @@ def run_video(video_file, conf=0.25):
         idx += 1; t = idx/fps
 
         res = yolo(frame, conf=conf)[0]
-        for box in res.boxes.xyxy.cpu().numpy().astype(int):
-            x1,y1,x2,y2 = box
-            crop = frame[y1:y2, x1:x2]
+        # YOLO’dan gelen tüm kutuları al
+        boxes = res.boxes.xyxy.cpu().numpy().astype(int)
+        if len(boxes):
+            # genişlik*yükseklik’e göre en büyüğü seç
+            w = boxes[:,2] - boxes[:,0]
+            h = boxes[:,3] - boxes[:,1]
+            idx = int(np.argmax(w * h))
+            x1,y1,x2,y2 = boxes[idx]
+            crop = out[y1:y2, x1:x2]
+
             if crop.size == 0: continue
 
             plate_img = cv2.resize(crop, (128,32))