diff --git a/counter_live_rknn.py b/counter_live_rknn.py
index 4d98bd9..f4045f3 100644
--- a/counter_live_rknn.py
+++ b/counter_live_rknn.py
@@ -3,6 +3,7 @@ Edge production live counter — RTSP + YOLO RKNN + line crossing.
 Runs on RK3588 hardware with RKNN model (320×320 input).
 Replaces the Jetson/TensorRT variant.
 """
+
 import numpy as np
 import cv2
 import csv
@@ -13,68 +14,73 @@ from datetime import datetime
 from pathlib import Path
 
 from dotenv import load_dotenv
+
 load_dotenv()
 
 from rknnlite.api import RKNNLite
 from batch_store import BatchStore
 
 # --- config (override via env / .env) ---
-OUTPUT_DIR = os.getenv('OUTPUT_DIR', '/opt/jetson-counter')
-DB_PATH = os.getenv('DB_PATH', f'{OUTPUT_DIR}/jetson_counter.db')
-STATE_FILE = os.getenv('STATE_FILE', f'{OUTPUT_DIR}/current_batch.json')
-SOURCE = os.getenv('SOURCE', 'rtsp://user:pass@192.168.0.100:554/stream1')
-MODEL_PATH = os.getenv('MODEL_PATH', '/opt/jetson-counter/yolo11n.rknn')
-CAMERA_NAME = os.getenv('CAMERA_NAME', 'CC1')
-OBJECT_LABEL = os.getenv('OBJECT_LABEL', 'ayam-potong')
-CLASS_AYAM = os.getenv('CLASS_AYAM', 'ayam')
-CLASS_TALENAN = os.getenv('CLASS_TALENAN', 'talenan')
+OUTPUT_DIR = os.getenv("OUTPUT_DIR", "/opt/jetson-counter")
+DB_PATH = os.getenv("DB_PATH", f"{OUTPUT_DIR}/jetson_counter.db")
+STATE_FILE = os.getenv("STATE_FILE", f"{OUTPUT_DIR}/current_batch.json")
+SOURCE = os.getenv("SOURCE", "rtsp://user:pass@192.168.0.100:554/stream1")
+MODEL_PATH = os.getenv("MODEL_PATH", "/opt/jetson-counter/yolo11n.rknn")
+CAMERA_NAME = os.getenv("CAMERA_NAME", "CC1")
+OBJECT_LABEL = os.getenv("OBJECT_LABEL", "ayam-potong")
+CLASS_AYAM = os.getenv("CLASS_AYAM", "ayam")
+CLASS_TALENAN = os.getenv("CLASS_TALENAN", "talenan")
 
-LINE_X = int(os.getenv('LINE_X')) if os.getenv('LINE_X') else None
-LINE_X_FRAC = float(os.getenv('LINE_X_FRAC', '0.5'))
-CROSS_DIRECTION = os.getenv('CROSS_DIRECTION', 'rtl').lower()
+LINE_X = int(os.getenv("LINE_X")) if os.getenv("LINE_X") else None
+LINE_X_FRAC = float(os.getenv("LINE_X_FRAC", "0.5"))
+CROSS_DIRECTION = os.getenv("CROSS_DIRECTION", "rtl").lower()
 
-IMGSZ = int(os.getenv('IMGSZ', '320'))
-HALF = os.getenv('HALF', 'false').lower() == 'true'
-CONF = float(os.getenv('CONF', '0.3'))
-DEVICE = int(os.getenv('DEVICE', '0'))
+IMGSZ = int(os.getenv("IMGSZ", "320"))
+HALF = os.getenv("HALF", "false").lower() == "true"
+CONF = float(os.getenv("CONF", "0.3"))
+DEVICE = int(os.getenv("DEVICE", "0"))
 
 # RKNN-specific — core mask for NPU
 # 1 = core0, 2 = core1, 3 = core0+core1 (dual), 7 = all three
-CORE_MASK = int(os.getenv('CORE_MASK', '1'))
+CORE_MASK = int(os.getenv("CORE_MASK", "1"))
 
 # YOLO decoder config
-NUM_CLASSES = int(os.getenv('NUM_CLASSES', '2'))
-SCORE_SIGMOID = os.getenv('SCORE_SIGMOID', 'false').lower() == 'true'
+NUM_CLASSES = int(os.getenv("NUM_CLASSES", "2"))
+SCORE_SIGMOID = os.getenv("SCORE_SIGMOID", "false").lower() == "true"
 
-DAILY_CUTOFF_TIME = os.getenv('DAILY_CUTOFF_TIME', '20:00')
-BATCH_TIMEOUT_SECONDS = float(os.getenv('BATCH_TIMEOUT_SECONDS', '300'))
-IGNORE_BATCH_LABEL_TIMEOUT = float(os.getenv('IGNORE_BATCH_LABEL_TIMEOUT_SECONDS', '30'))
-MIN_OBJECT_PER_BATCH = int(os.getenv('MIN_OBJECT_PER_BATCH', '60'))
-MIN_DURATION_PER_BATCH = int(os.getenv('MIN_DURATION_PER_BATCH', '60'))
+DAILY_CUTOFF_TIME = os.getenv("DAILY_CUTOFF_TIME", "20:00")
+BATCH_TIMEOUT_SECONDS = float(os.getenv("BATCH_TIMEOUT_SECONDS", "300"))
+IGNORE_BATCH_LABEL_TIMEOUT = float(
+    os.getenv("IGNORE_BATCH_LABEL_TIMEOUT_SECONDS", "30")
+)
+MIN_OBJECT_PER_BATCH = int(os.getenv("MIN_OBJECT_PER_BATCH", "60"))
+MIN_DURATION_PER_BATCH = int(os.getenv("MIN_DURATION_PER_BATCH", "60"))
 
-EXPORT_CSV = os.getenv('EXPORT_CSV', 'true').lower() == 'true'
-CROSS_CSV = os.getenv('CROSS_CSV', f'{OUTPUT_DIR}/batch_crossings.csv')
+EXPORT_CSV = os.getenv("EXPORT_CSV", "true").lower() == "true"
+CROSS_CSV = os.getenv("CROSS_CSV", f"{OUTPUT_DIR}/batch_crossings.csv")
 
-WARMUP_FRAMES = int(os.getenv('WARMUP_FRAMES', '30'))
-RECONNECT_DELAY_SEC = int(os.getenv('RECONNECT_DELAY_SEC', '3'))
-MAX_RECONNECT_ATTEMPTS = int(os.getenv('MAX_RECONNECT_ATTEMPTS', '0'))
-FLUSH_EVERY_N_FRAMES = int(os.getenv('FLUSH_EVERY_N_FRAMES', '100'))
-TRACKED_PRUNE_SEC = int(os.getenv('TRACKED_PRUNE_SEC', '300'))
-RECORD_VIDEO = os.getenv('RECORD_VIDEO', 'false').lower() == 'true'
-VIDEO_SEGMENT_SEC = int(os.getenv('VIDEO_SEGMENT_SEC', '3600'))
-OUTPUT_FPS = int(os.getenv('OUTPUT_FPS', '15'))
+WARMUP_FRAMES = int(os.getenv("WARMUP_FRAMES", "30"))
+RECONNECT_DELAY_SEC = int(os.getenv("RECONNECT_DELAY_SEC", "3"))
+MAX_RECONNECT_ATTEMPTS = int(os.getenv("MAX_RECONNECT_ATTEMPTS", "0"))
+FLUSH_EVERY_N_FRAMES = int(os.getenv("FLUSH_EVERY_N_FRAMES", "100"))
+TRACKED_PRUNE_SEC = int(os.getenv("TRACKED_PRUNE_SEC", "300"))
+RECORD_VIDEO = os.getenv("RECORD_VIDEO", "false").lower() == "true"
+VIDEO_SEGMENT_SEC = int(os.getenv("VIDEO_SEGMENT_SEC", "3600"))
+OUTPUT_FPS = int(os.getenv("OUTPUT_FPS", "15"))
 
-LIVE_STREAM_ENABLED = os.getenv('LIVE_STREAM_ENABLED', 'false').lower() == 'true'
-LIVE_STREAM_FRAME_PATH = os.getenv('LIVE_STREAM_FRAME_PATH', '/dev/shm/jetson-counter/live_frame.jpg')
-LIVE_STREAM_QUALITY = int(os.getenv('LIVE_STREAM_QUALITY', '75'))
-LIVE_STREAM_EVERY_N = int(os.getenv('LIVE_STREAM_EVERY_N', '2'))
+LIVE_STREAM_ENABLED = os.getenv("LIVE_STREAM_ENABLED", "false").lower() == "true"
+LIVE_STREAM_FRAME_PATH = os.getenv(
+    "LIVE_STREAM_FRAME_PATH", "/dev/shm/jetson-counter/live_frame.jpg"
+)
+LIVE_STREAM_QUALITY = int(os.getenv("LIVE_STREAM_QUALITY", "75"))
+LIVE_STREAM_EVERY_N = int(os.getenv("LIVE_STREAM_EVERY_N", "2"))
 
 RTSP_FFMPEG_OPTIONS = os.getenv(
-    'OPENCV_FFMPEG_CAPTURE_OPTIONS',
-    'rtsp_transport;tcp|fflags;nobuffer|flags;low_delay',
+    "OPENCV_FFMPEG_CAPTURE_OPTIONS",
+    "rtsp_transport;tcp|fflags;nobuffer|flags;low_delay",
 )
 
-IS_LIVE = SOURCE.lower().startswith(('rtsp://', 'http://'))
+IS_LIVE = SOURCE.lower().startswith(("rtsp://", "http://"))
 
 CROSS_FLASH_FRAMES = 12
 POPUP_LIFETIME = 20
@@ -84,8 +90,14 @@ BATCH_PULSE_FRAMES = 20
 
 SKELETON = [(0, 1), (4, 3), (1, 2), (3, 2), (2, 6), (2, 5), (2, 7), (7, 8)]
 SK_COLORS = [
-    (0, 255, 255), (0, 255, 255), (255, 0, 255), (255, 0, 255),
-    (0, 255, 0), (255, 255, 0), (0, 0, 255), (200, 200, 0),
+    (0, 255, 255),
+    (0, 255, 255),
+    (255, 0, 255),
+    (255, 0, 255),
+    (0, 255, 0),
+    (255, 255, 0),
+    (0, 0, 255),
+    (200, 200, 0),
 ]
 
 C_PANEL = (28, 24, 18)
@@ -105,7 +117,7 @@ shutdown_requested = False
 def request_shutdown(signum, frame):
     global shutdown_requested
     shutdown_requested = True
-    print('\nShutdown requested — finishing current frame...')
+    print("\nShutdown requested — finishing current frame...")
 
 
 signal.signal(signal.SIGINT, request_shutdown)
@@ -116,6 +128,7 @@ signal.signal(signal.SIGTERM, request_shutdown)
 # YOLO output decoder (NMS only — boxes are pre-decoded by the model)
 # =============================================================================
 
+
 def _nms(boxes, scores, iou_thr=0.45):
     order = np.argsort(scores)[::-1]
     keep = []
@@ -132,7 +145,9 @@ def _nms(boxes, scores, iou_thr=0.45):
         h = np.maximum(0.0, yy2 - yy1)
         inter = w * h
         area_i = (boxes[idx, 2] - boxes[idx, 0]) * (boxes[idx, 3] - boxes[idx, 1])
-        area_o = (boxes[order[1:], 2] - boxes[order[1:], 0]) * (boxes[order[1:], 3] - boxes[order[1:], 1])
+        area_o = (boxes[order[1:], 2] - boxes[order[1:], 0]) * (
+            boxes[order[1:], 3] - boxes[order[1:], 1]
+        )
         iou = inter / (area_i + area_o - inter + 1e-16)
         order = order[1:][iou < iou_thr]
     return np.array(keep)
@@ -164,12 +179,13 @@ def _compute_iou(box1, boxes2):
 # Simple IoU tracker (replaces bytetrack — same persist behaviour)
 # =============================================================================
 
+
 class SimpleTracker:
     def __init__(self, max_age=30, min_hits=1, iou_threshold=0.3):
         self.max_age = max_age
         self.min_hits = min_hits
         self.iou_threshold = iou_threshold
-        self.tracks = {}       # track_id -> {box, cx, age, hits, time_since_update}
+        self.tracks = {}  # track_id -> {box, cx, age, hits, time_since_update}
         self.next_id = 1
 
     def update(self, detections):
@@ -177,33 +193,41 @@ class SimpleTracker:
         now = time.monotonic()
 
         for tid in self.tracks:
-            self.tracks[tid]['time_since_update'] += 1
+            self.tracks[tid]["time_since_update"] += 1
 
         matched_det = set()
         matched_track = set()
-        assignments = []   # (track_id, det_idx)
+        assignments = []  # (track_id, det_idx)
         det_to_track = {}  # det_idx → track_id
 
         if detections and self.tracks:
             track_ids = list(self.tracks.keys())
-            track_boxes = np.stack([self.tracks[t]['box'] for t in track_ids], axis=0)
+            track_boxes = np.stack([self.tracks[t]["box"] for t in track_ids], axis=0)
 
             for di, det in enumerate(detections):
                 _, det_box = det
-                ious = np.array([_compute_iou(det_box, track_boxes[t:t + 1]) for t in range(len(track_ids))])
+                ious = np.array(
+                    [
+                        _compute_iou(det_box, track_boxes[t : t + 1])
+                        for t in range(len(track_ids))
+                    ]
+                )
                 best_j = int(np.argmax(ious))
-                if ious[best_j] >= self.iou_threshold and track_ids[best_j] not in matched_track:
+                if (
+                    ious[best_j] >= self.iou_threshold
+                    and track_ids[best_j] not in matched_track
+                ):
                     assignments.append((track_ids[best_j], di))
                     matched_track.add(track_ids[best_j])
                     matched_det.add(di)
 
         for tid, di in assignments:
             cx, box = detections[di]
-            self.tracks[tid]['cx'] = cx
-            self.tracks[tid]['box'] = box
-            self.tracks[tid]['hits'] += 1
-            self.tracks[tid]['time_since_update'] = 0
-            self.tracks[tid]['last_update'] = now
+            self.tracks[tid]["cx"] = cx
+            self.tracks[tid]["box"] = box
+            self.tracks[tid]["hits"] += 1
+            self.tracks[tid]["time_since_update"] = 0
+            self.tracks[tid]["last_update"] = now
             det_to_track[di] = tid
 
         for di, det in enumerate(detections):
@@ -212,19 +236,27 @@ class SimpleTracker:
                 new_id = self.next_id
                 self.next_id += 1
                 self.tracks[new_id] = {
-                    'cx': cx, 'box': box, 'hits': 1,
-                    'time_since_update': 0, 'last_update': now,
+                    "cx": cx,
+                    "box": box,
+                    "hits": 1,
+                    "time_since_update": 0,
+                    "last_update": now,
                 }
                 det_to_track[di] = new_id
 
-        stale = [tid for tid, t in self.tracks.items()
-                 if t['time_since_update'] > self.max_age]
+        stale = [
+            tid
+            for tid, t in self.tracks.items()
+            if t["time_since_update"] > self.max_age
+        ]
         for tid in stale:
             del self.tracks[tid]
 
-        track_map = {tid: self.tracks[tid]['cx']
-                     for tid in self.tracks
-                     if self.tracks[tid]['hits'] >= self.min_hits}
+        track_map = {
+            tid: self.tracks[tid]["cx"]
+            for tid in self.tracks
+            if self.tracks[tid]["hits"] >= self.min_hits
+        }
         return track_map, det_to_track
 
 
@@ -232,9 +264,19 @@ class SimpleTracker:
 # RKNN YOLO wrapper (detect output format: (1, 4+num_classes, N))
 # =============================================================================
 
+
 class RKNNYOLO:
-    def __init__(self, model_path, core_mask=1, imgsz=320, conf=0.3, iou=0.45,
-                 num_classes=2, num_keypoints=0, score_sigmoid=False):
+    def __init__(
+        self,
+        model_path,
+        core_mask=1,
+        imgsz=320,
+        conf=0.3,
+        iou=0.45,
+        num_classes=2,
+        num_keypoints=0,
+        score_sigmoid=False,
+    ):
         self.imgsz = imgsz
         self.conf = conf
         self.iou = iou
@@ -245,19 +287,20 @@ class RKNNYOLO:
         self.rknn = RKNNLite(verbose=False)
         ret = self.rknn.load_rknn(model_path)
         if ret != 0:
-            raise RuntimeError(f'Failed to load RKNN model: {model_path}')
+            raise RuntimeError(f"Failed to load RKNN model: {model_path}")
         ret = self.rknn.init_runtime(core_mask=core_mask)
         if ret != 0:
-            raise RuntimeError(f'Failed to init RKNN runtime (core_mask={core_mask})')
+            raise RuntimeError(f"Failed to init RKNN runtime (core_mask={core_mask})")
 
         try:
             from rknnlite.api import RKNNLite as _RK
+
             sdk_ver = self.rknn.get_sdk_version()
-            print(f'RKNN SDK version: {sdk_ver}')
+            print(f"RKNN SDK version: {sdk_ver}")
         except Exception:
             pass
 
-        print(f'RKNN model loaded: {model_path}  imgsz={imgsz}  core_mask={core_mask}')
+        print(f"RKNN model loaded: {model_path}  imgsz={imgsz}  core_mask={core_mask}")
 
     def _preprocess(self, frame):
         """Letterbox-resize to imgsz×imgsz, maintain aspect ratio, BGR→RGB, normalize."""
@@ -269,7 +312,7 @@ class RKNNYOLO:
         letterbox = np.full((self.imgsz, self.imgsz, 3), 114, dtype=np.uint8)
         dy = (self.imgsz - nh) // 2
         dx = (self.imgsz - nw) // 2
-        letterbox[dy:dy + nh, dx:dx + nw] = resized
+        letterbox[dy : dy + nh, dx : dx + nw] = resized
 
         rgb = cv2.cvtColor(letterbox, cv2.COLOR_BGR2RGB)
         gains = np.array([scale, scale, dy, dx], dtype=np.float32)
@@ -295,7 +338,7 @@ class RKNNYOLO:
         if out.shape[0] == self.num_classes + 4:
             out = out.T  # (C, N) → (N, C)
 
-        boxes_cxcywh = out[:, :4].copy()   # cx, cy, w, h at model resolution
+        boxes_cxcywh = out[:, :4].copy()  # cx, cy, w, h at model resolution
         cls_raw = out[:, 4:].copy()
 
         if self.score_sigmoid:
@@ -303,12 +346,15 @@ class RKNNYOLO:
         else:
             cls_scores = cls_raw
 
-        boxes_xyxy = np.stack([
-            boxes_cxcywh[:, 0] - boxes_cxcywh[:, 2] / 2,
-            boxes_cxcywh[:, 1] - boxes_cxcywh[:, 3] / 2,
-            boxes_cxcywh[:, 0] + boxes_cxcywh[:, 2] / 2,
-            boxes_cxcywh[:, 1] + boxes_cxcywh[:, 3] / 2,
-        ], axis=1)
+        boxes_xyxy = np.stack(
+            [
+                boxes_cxcywh[:, 0] - boxes_cxcywh[:, 2] / 2,
+                boxes_cxcywh[:, 1] - boxes_cxcywh[:, 3] / 2,
+                boxes_cxcywh[:, 0] + boxes_cxcywh[:, 2] / 2,
+                boxes_cxcywh[:, 1] + boxes_cxcywh[:, 3] / 2,
+            ],
+            axis=1,
+        )
 
         max_scores = cls_scores.max(axis=1)
         class_ids = cls_scores.argmax(axis=1)
@@ -339,12 +385,14 @@ class RKNNYOLO:
             keep = _nms(bboxes[idx], scores[idx], iou_thr=self.iou)
             for k in keep:
                 j = idx[k]
-                detections.append({
-                    'bbox': bboxes[j].tolist(),
-                    'score': float(scores[j]),
-                    'cls': int(clses[j]),
-                    'keypoints': None,
-                })
+                detections.append(
+                    {
+                        "bbox": bboxes[j].tolist(),
+                        "score": float(scores[j]),
+                        "cls": int(clses[j]),
+                        "keypoints": None,
+                    }
+                )
         return detections
 
     def release(self):
@@ -365,41 +413,41 @@ def resolve_line_x(frame_width):
 
 
 def crossed_line(prev_cx, cx, line_x, direction=CROSS_DIRECTION):
-    if direction == 'ltr':
+    if direction == "ltr":
         return prev_cx < line_x <= cx
-    if direction == 'both':
+    if direction == "both":
         return (prev_cx > line_x >= cx) or (prev_cx < line_x <= cx)
     return prev_cx > line_x >= cx
 
 
 def now_str():
-    return datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
 
 def open_capture(source):
-    if source.lower().startswith(('rtsp://', 'http://')):
-        os.environ['OPENCV_FFMPEG_CAPTURE_OPTIONS'] = RTSP_FFMPEG_OPTIONS
+    if source.lower().startswith(("rtsp://", "http://")):
+        os.environ["OPENCV_FFMPEG_CAPTURE_OPTIONS"] = RTSP_FFMPEG_OPTIONS
     cap = cv2.VideoCapture(source, cv2.CAP_FFMPEG)
     cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
     return cap
 
 
 def warmup_stream(cap, n=WARMUP_FRAMES):
-    print('Warming up stream...')
+    print("Warming up stream...")
     for _ in range(n):
         cap.read()
-    print('Stream ready!')
+    print("Stream ready!")
 
 
 def open_video_writer(path, w, h, fps):
-    return cv2.VideoWriter(path, cv2.VideoWriter_fourcc(*'avc1'), fps, (w, h))
+    return cv2.VideoWriter(path, cv2.VideoWriter_fourcc(*"avc1"), fps, (w, h))
 
 
 class CsvLogger:
     def __init__(self, path, header):
         Path(path).parent.mkdir(parents=True, exist_ok=True)
         new_file = not Path(path).exists() or Path(path).stat().st_size == 0
-        self.file = open(path, 'a', newline='', buffering=1)
+        self.file = open(path, "a", newline="", buffering=1)
         self.writer = csv.writer(self.file)
         if new_file:
             self.writer.writerow(header)
@@ -424,8 +472,8 @@ class VideoSegmentWriter:
         self._open_next()
 
     def _segment_path(self):
-        ts = datetime.now().strftime('%Y%m%d_%H%M%S')
-        return str(self.output_dir / f'live_{ts}.mp4')
+        ts = datetime.now().strftime("%Y%m%d_%H%M%S")
+        return str(self.output_dir / f"live_{ts}.mp4")
 
     def _open_next(self):
         if self.writer is not None:
@@ -433,7 +481,7 @@ class VideoSegmentWriter:
         path = self._segment_path()
         self.writer = open_video_writer(path, self.w, self.h, self.fps)
         self.segment_start = time.monotonic()
-        print(f'Recording segment: {path}')
+        print(f"Recording segment: {path}")
 
     def write(self, frame):
         if time.monotonic() - self.segment_start >= self.segment_sec:
@@ -446,7 +494,9 @@ class VideoSegmentWriter:
 
 
 def prune_stale_tracks(tracked, now_mono):
-    stale = [tid for tid, (_, ts) in tracked.items() if now_mono - ts > TRACKED_PRUNE_SEC]
+    stale = [
+        tid for tid, (_, ts) in tracked.items() if now_mono - ts > TRACKED_PRUNE_SEC
+    ]
     for tid in stale:
         del tracked[tid]
 
@@ -484,7 +534,16 @@ def draw_elegant_counting_line(img, line_x, h, pulse_remaining=0):
         y_end = min(y + dash_len, h)
         cv2.line(img, (line_x, y), (line_x, y_end), C_LINE_CORE, 2, cv2.LINE_AA)
         y += dash_len + gap
-    cv2.putText(img, 'COUNT LINE', (line_x - 46, 24), cv2.FONT_HERSHEY_SIMPLEX, 0.42, C_LINE_CORE, 1, cv2.LINE_AA)
+    cv2.putText(
+        img,
+        "COUNT LINE",
+        (line_x - 46, 24),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.42,
+        C_LINE_CORE,
+        1,
+        cv2.LINE_AA,
+    )
 
 
 def draw_hero_count(img, line_x, h, count, pulse_remaining=0):
@@ -495,34 +554,120 @@ def draw_hero_count(img, line_x, h, count, pulse_remaining=0):
     (tw, th), _ = cv2.getTextSize(text, font, font_scale, thickness)
     pad = 14
     tx, ty = line_x - tw // 2, h // 2 + th // 2
-    overlay_rect(img, tx - pad, ty - th - pad, tx + tw + pad, ty + pad // 2, C_PANEL, alpha=0.78)
-    cv2.rectangle(img, (tx - pad, ty - th - pad), (tx + tw + pad, ty + pad // 2), C_LINE_CORE, 2)
+    overlay_rect(
+        img, tx - pad, ty - th - pad, tx + tw + pad, ty + pad // 2, C_PANEL, alpha=0.78
+    )
+    cv2.rectangle(
+        img, (tx - pad, ty - th - pad), (tx + tw + pad, ty + pad // 2), C_LINE_CORE, 2
+    )
     cv2.putText(img, text, (tx, ty), font, font_scale, C_GREEN, thickness, cv2.LINE_AA)
 
 
-def draw_hud(img, w, batch_num, batch_count, total_ayam, elapsed_sec, rate, camera_id, clock):
+def draw_hud(
+    img, w, batch_num, batch_count, total_ayam, elapsed_sec, rate, camera_id, clock
+):
     bar_h = 52
     overlay_rect(img, 0, 0, w, bar_h, C_PANEL, alpha=0.72)
     cv2.line(img, (0, bar_h), (w, bar_h), C_BORDER, 1)
-    cv2.putText(img, 'BATCH', (16, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    batch_label = str(batch_num) if batch_num else '—'
-    cv2.putText(img, batch_label, (16, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.9, C_ACCENT, 2, cv2.LINE_AA)
-    cv2.putText(img, 'COUNT', (100, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    cv2.putText(img, str(batch_count), (100, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.9, C_GREEN, 2, cv2.LINE_AA)
-    cv2.putText(img, 'TOTAL', (190, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    cv2.putText(img, str(total_ayam), (190, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.7, C_TEXT, 1, cv2.LINE_AA)
-    cv2.putText(img, 'UPTIME', (280, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    cv2.putText(img, f'{elapsed_sec / 3600:.1f}h', (280, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.7, C_TEXT, 1, cv2.LINE_AA)
-    cv2.putText(img, 'RATE', (380, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    cv2.putText(img, f'{rate:.1f}/min', (380, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.7, C_ACCENT, 1, cv2.LINE_AA)
-    cv2.putText(img, clock, (w - 180, 36), cv2.FONT_HERSHEY_SIMPLEX, 0.55, C_TEXT, 1, cv2.LINE_AA)
-    cv2.putText(img, f'CAM {camera_id}', (w - 180, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
+    cv2.putText(
+        img, "BATCH", (16, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+    )
+    batch_label = str(batch_num) if batch_num else "—"
+    cv2.putText(
+        img,
+        batch_label,
+        (16, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.9,
+        C_ACCENT,
+        2,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img, "COUNT", (100, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+    )
+    cv2.putText(
+        img,
+        str(batch_count),
+        (100, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.9,
+        C_GREEN,
+        2,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img, "TOTAL", (190, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+    )
+    cv2.putText(
+        img,
+        str(total_ayam),
+        (190, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.7,
+        C_TEXT,
+        1,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img,
+        "UPTIME",
+        (280, 20),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.45,
+        C_MUTED,
+        1,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img,
+        f"{elapsed_sec / 3600:.1f}h",
+        (280, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.7,
+        C_TEXT,
+        1,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img, "RATE", (380, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+    )
+    cv2.putText(
+        img,
+        f"{rate:.1f}/min",
+        (380, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.7,
+        C_ACCENT,
+        1,
+        cv2.LINE_AA,
+    )
+    # cv2.putText(img, clock, (w - 180, 36), cv2.FONT_HERSHEY_SIMPLEX, 0.55, C_TEXT, 1, cv2.LINE_AA)
+    cv2.putText(
+        img,
+        f"CAM {camera_id}",
+        (w - 180, 20),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.45,
+        C_MUTED,
+        1,
+        cv2.LINE_AA,
+    )
 
 
 def draw_footer(img, w, h, frame_idx, live_tag):
     bar_h = 28
     overlay_rect(img, 0, h - bar_h, w, h, C_PANEL, alpha=0.55)
-    cv2.putText(img, f'{live_tag} | Frame {frame_idx}', (12, h - 9), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
+    cv2.putText(
+        img,
+        f"{live_tag} | Frame {frame_idx}",
+        (12, h - 9),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.45,
+        C_MUTED,
+        1,
+        cv2.LINE_AA,
+    )
 
 
 def draw_skeleton_bold(img, kpts):
@@ -542,28 +687,39 @@ def draw_skeleton_bold(img, kpts):
 def draw_popups(img, popups, frame_idx):
     alive = []
     for pop in popups:
-        age = frame_idx - pop['born']
+        age = frame_idx - pop["born"]
         if age > POPUP_LIFETIME:
             continue
         alive.append(pop)
         fade = 1.0 - age / POPUP_LIFETIME
-        y = pop['y'] - int(age * 1.8)
+        y = pop["y"] - int(age * 1.8)
         color = (int(C_GREEN[0] * fade), int(C_GREEN[1] * fade), int(C_GREEN[2] * fade))
-        cv2.putText(img, pop['text'], (pop['x'], y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, color, 2, cv2.LINE_AA)
+        cv2.putText(
+            img,
+            pop["text"],
+            (pop["x"], y),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            0.7,
+            color,
+            2,
+            cv2.LINE_AA,
+        )
     return alive
 
 
 def draw_batch_banner(img, w, batch_num, pulse_remaining):
     if pulse_remaining <= 0:
         return
-    text = f'NEW BATCH {batch_num}'
+    text = f"NEW BATCH {batch_num}"
     font = cv2.FONT_HERSHEY_SIMPLEX
     (tw, th), _ = cv2.getTextSize(text, font, 0.8, 2)
     x1, y1 = w // 2 - tw // 2 - 16, 62
     x2, y2 = w // 2 + tw // 2 + 16, 62 + th + 20
     overlay_rect(img, x1, y1, x2, y2, C_PANEL, alpha=0.7)
     cv2.rectangle(img, (x1, y1), (x2, y2), C_ACCENT, 2)
-    cv2.putText(img, text, (w // 2 - tw // 2, 62 + th + 4), font, 0.8, C_ACCENT, 2, cv2.LINE_AA)
+    cv2.putText(
+        img, text, (w // 2 - tw // 2, 62 + th + 4), font, 0.8, C_ACCENT, 2, cv2.LINE_AA
+    )
 
 
 def connect_stream(source, warmup=WARMUP_FRAMES):
@@ -573,11 +729,13 @@ def connect_stream(source, warmup=WARMUP_FRAMES):
         if not cap.isOpened():
             attempts += 1
             if MAX_RECONNECT_ATTEMPTS and attempts >= MAX_RECONNECT_ATTEMPTS:
-                raise RuntimeError(f'Cannot open source after {attempts} attempts: {source}')
-            print(f'Cannot open source, retry in {RECONNECT_DELAY_SEC}s...')
+                raise RuntimeError(
+                    f"Cannot open source after {attempts} attempts: {source}"
+                )
+            print(f"Cannot open source, retry in {RECONNECT_DELAY_SEC}s...")
             time.sleep(RECONNECT_DELAY_SEC)
             continue
-        if warmup > 0 and source.lower().startswith(('rtsp://', 'http://')):
+        if warmup > 0 and source.lower().startswith(("rtsp://", "http://")):
             warmup_stream(cap, warmup)
         w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
         h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
@@ -592,6 +750,7 @@ def connect_stream(source, warmup=WARMUP_FRAMES):
 # Main loop
 # =============================================================================
 
+
 def run():
     global shutdown_requested
 
@@ -605,13 +764,15 @@ def run():
         ignore_batch_label_timeout=IGNORE_BATCH_LABEL_TIMEOUT,
         min_object_per_batch=MIN_OBJECT_PER_BATCH,
         min_duration_per_batch=MIN_DURATION_PER_BATCH,
-        logger=lambda msg: print(f'[{now_str()}] {msg}'),
+        logger=lambda msg: print(f"[{now_str()}] {msg}"),
     )
     store.start_cutoff_watcher()
 
     cross_logger = None
     if EXPORT_CSV:
-        cross_logger = CsvLogger(CROSS_CSV, ['batch', 'frame', 'timestamp', 'chicken_id'])
+        cross_logger = CsvLogger(
+            CROSS_CSV, ["batch", "frame", "timestamp", "chicken_id"]
+        )
 
     # Load RKNN model
     model = RKNNYOLO(
@@ -627,8 +788,8 @@ def run():
     # class index 0 → CLASS_AYAM, index 1 → CLASS_TALENAN (or env-specified)
     # Use class names in env order: first CLASS_AYAM → id 0, then CLASS_TALENAN → id 1
     CLASS_IDS = {
-        os.getenv('CLASS_AYAM', 'ayam'): 0,
-        os.getenv('CLASS_TALENAN', 'talenan'): 1,
+        os.getenv("CLASS_AYAM", "ayam"): 0,
+        os.getenv("CLASS_TALENAN", "talenan"): 1,
     }
     ayam_cls = CLASS_IDS[CLASS_AYAM]
     talenan_cls = CLASS_IDS[CLASS_TALENAN]
@@ -655,10 +816,12 @@ def run():
         return
 
     line_x = resolve_line_x(w)
-    print(f'RKNN counter | {w}x{h} @ {fps}fps | line x={line_x} | cross={CROSS_DIRECTION}')
-    print(f'Model: {MODEL_PATH} | imgsz={IMGSZ} | core_mask={CORE_MASK}')
-    print(f'DB: {DB_PATH}')
-    print(f'State: {STATE_FILE}')
+    print(
+        f"RKNN counter | {w}x{h} @ {fps}fps | line x={line_x} | cross={CROSS_DIRECTION}"
+    )
+    print(f"Model: {MODEL_PATH} | imgsz={IMGSZ} | core_mask={CORE_MASK}")
+    print(f"DB: {DB_PATH}")
+    print(f"State: {STATE_FILE}")
 
     if RECORD_VIDEO:
         video_writer = VideoSegmentWriter(OUTPUT_DIR, w, h, fps, VIDEO_SEGMENT_SEC)
@@ -671,7 +834,9 @@ def run():
             if not IS_LIVE:
                 break
             reconnect_count += 1
-            print(f'Stream dropped (attempt {reconnect_count}), reconnecting in {RECONNECT_DELAY_SEC}s...')
+            print(
+                f"Stream dropped (attempt {reconnect_count}), reconnecting in {RECONNECT_DELAY_SEC}s..."
+            )
             cap.release()
             time.sleep(RECONNECT_DELAY_SEC)
             cap, w, h, fps = connect_stream(SOURCE)
@@ -691,12 +856,12 @@ def run():
         if detections:
             ayam_dets = []  # list of (cx, xywh_box)
             talenan_dets = []
-            ayam_kpts_map = {}   # det_idx → keypoints
+            ayam_kpts_map = {}  # det_idx → keypoints
             talenan_kpts_map = {}
 
             for di, det in enumerate(detections):
-                bbox = det['bbox']
-                cls_id = det['cls']
+                bbox = det["bbox"]
+                cls_id = det["cls"]
                 cx = (bbox[0] + bbox[2]) / 2.0
                 x1, y1, x2, y2 = bbox
                 wb, hb = x2 - x1, y2 - y1
@@ -704,12 +869,12 @@ def run():
 
                 if cls_id == talenan_cls:
                     talenan_dets.append((cx, box_cxcywh))
-                    if det['keypoints'] is not None:
-                        talenan_kpts_map[len(talenan_dets) - 1] = det['keypoints']
+                    if det["keypoints"] is not None:
+                        talenan_kpts_map[len(talenan_dets) - 1] = det["keypoints"]
                 elif cls_id == ayam_cls:
                     ayam_dets.append((cx, box_cxcywh))
-                    if det['keypoints'] is not None:
-                        ayam_kpts_map[len(ayam_dets) - 1] = det['keypoints']
+                    if det["keypoints"] is not None:
+                        ayam_kpts_map[len(ayam_dets) - 1] = det["keypoints"]
 
             # Track ayam — returns (track_id → cx, detection_idx → track_id)
             ayam_cx_map, ayam_det_to_track = ayam_tracker.update(ayam_dets)
@@ -725,17 +890,22 @@ def run():
                 if tid in talenan_tracker.tracks:
                     if tid in talenan_tracked:
                         prev_cx = talenan_tracked[tid][0]
-                        if crossed_line(prev_cx, cx, line_x) and tid not in talenan_line_crossed:
+                        if (
+                            crossed_line(prev_cx, cx, line_x)
+                            and tid not in talenan_line_crossed
+                        ):
                             talenan_line_crossed.add(tid)
                             if store.record_talenan_crossing(tid):
                                 batch_closed_frame = True
                                 talenan_cross_flash[tid] = CROSS_FLASH_FRAMES
-                                popups.append({
-                                    'x': int(cx) - 20,
-                                    'y': int(box[1]),
-                                    'born': frame_idx,
-                                    'text': 'BATCH CLOSED',
-                                })
+                                popups.append(
+                                    {
+                                        "x": int(cx) - 20,
+                                        "y": int(box[1]),
+                                        "born": frame_idx,
+                                        "text": "BATCH CLOSED",
+                                    }
+                                )
                     talenan_tracked[tid] = (cx, mono)
 
             # Process ayam crossings
@@ -746,24 +916,33 @@ def run():
                 if tid in ayam_tracker.tracks:
                     if tid in ayam_tracked:
                         prev_cx = ayam_tracked[tid][0]
-                        if crossed_line(prev_cx, cx, line_x) and tid not in ayam_line_crossed:
+                        if (
+                            crossed_line(prev_cx, cx, line_x)
+                            and tid not in ayam_line_crossed
+                        ):
                             ayam_line_crossed.add(tid)
                             _, started_new = store.record_ayam_crossing(tid)
                             if cross_logger:
-                                cross_logger.write_row([
-                                    store.current_batch_number, frame_idx,
-                                    datetime.now().isoformat(), tid,
-                                ])
+                                cross_logger.write_row(
+                                    [
+                                        store.current_batch_number,
+                                        frame_idx,
+                                        datetime.now().isoformat(),
+                                        tid,
+                                    ]
+                                )
                             ayam_crossed_frame = True
                             if started_new:
                                 batch_started_frame = True
                             ayam_cross_flash[tid] = CROSS_FLASH_FRAMES
-                            popups.append({
-                                'x': int(cx) - 12,
-                                'y': int(box[1]),
-                                'born': frame_idx,
-                                'text': '+1',
-                            })
+                            popups.append(
+                                {
+                                    "x": int(cx) - 12,
+                                    "y": int(box[1]),
+                                    "born": frame_idx,
+                                    "text": "+1",
+                                }
+                            )
                     ayam_tracked[tid] = (cx, mono)
 
             # Draw talenan
@@ -778,7 +957,7 @@ def run():
                 flash = talenan_cross_flash.get(tid, 0)
                 color = C_GREEN if flash > 0 else C_TALENAN_BOX
                 cv2.rectangle(frame, (x1, y1), (x2, y2), color, 3 if flash > 0 else 2)
-                draw_pill(frame, f'TALENAN {tid}', x1, y1 - 4, color)
+                draw_pill(frame, f"TALENAN {tid}", x1, y1 - 4, color)
 
             # Draw ayam
             for di, (cx, box) in enumerate(ayam_dets):
@@ -792,7 +971,7 @@ def run():
                 flash = ayam_cross_flash.get(tid, 0)
                 color = C_GREEN if flash > 0 else C_AYAM_BOX
                 cv2.rectangle(frame, (x1, y1), (x2, y2), color, 3 if flash > 0 else 2)
-                draw_pill(frame, f'ID {tid}', x1, y1 - 4, color)
+                draw_pill(frame, f"ID {tid}", x1, y1 - 4, color)
                 kpts = ayam_kpts_map.get(di)
                 if kpts is not None:
                     draw_skeleton_bold(frame, kpts)
@@ -812,9 +991,19 @@ def run():
 
         draw_elegant_counting_line(frame, line_x, h, line_pulse)
         draw_hero_count(frame, line_x, h, batch_count, count_pulse)
-        draw_hud(frame, w, batch_num, batch_count, display_total, elapsed, rate, CAMERA_NAME, now_str())
+        draw_hud(
+            frame,
+            w,
+            batch_num,
+            batch_count,
+            display_total,
+            elapsed,
+            rate,
+            CAMERA_NAME,
+            now_str(),
+        )
         draw_batch_banner(frame, w, batch_num, batch_pulse)
-        draw_footer(frame, w, h, frame_idx, 'LIVE-RKNN' if IS_LIVE else 'FILE-RKNN')
+        draw_footer(frame, w, h, frame_idx, "LIVE-RKNN" if IS_LIVE else "FILE-RKNN")
         popups = draw_popups(frame, popups, frame_idx)
 
         for flash_store in (ayam_cross_flash, talenan_cross_flash):
@@ -832,8 +1021,10 @@ def run():
         if LIVE_STREAM_ENABLED and frame_idx % LIVE_STREAM_EVERY_N == 0:
             try:
                 Path(LIVE_STREAM_FRAME_PATH).parent.mkdir(parents=True, exist_ok=True)
-                _, jpeg = cv2.imencode('.jpg', frame, [cv2.IMWRITE_JPEG_QUALITY, LIVE_STREAM_QUALITY])
-                with open(LIVE_STREAM_FRAME_PATH, 'wb') as f:
+                _, jpeg = cv2.imencode(
+                    ".jpg", frame, [cv2.IMWRITE_JPEG_QUALITY, LIVE_STREAM_QUALITY]
+                )
+                with open(LIVE_STREAM_FRAME_PATH, "wb") as f:
                     f.write(jpeg.tobytes())
             except Exception:
                 pass
@@ -841,8 +1032,8 @@ def run():
         frame_idx += 1
         if frame_idx % FLUSH_EVERY_N_FRAMES == 0:
             print(
-                f'[{now_str()}] Frame {frame_idx} | Batch {batch_num}: {batch_count} '
-                f'| Total: {display_total} | Uptime {elapsed / 3600:.2f}h'
+                f"[{now_str()}] Frame {frame_idx} | Batch {batch_num}: {batch_count} "
+                f"| Total: {display_total} | Uptime {elapsed / 3600:.2f}h"
             )
         prune_stale_tracks(ayam_tracked, mono)
         prune_stale_tracks(talenan_tracked, mono)
@@ -855,8 +1046,8 @@ def run():
     model.release()
     store.shutdown()
 
-    print('\n=== Batch Summary (SQLite) ===')
-    print(f'Database: {DB_PATH}')
+    print("\n=== Batch Summary (SQLite) ===")
+    print(f"Database: {DB_PATH}")
 
 
 # Tracked state dicts: track_id → (cx, monotonic_time)
@@ -864,5 +1055,5 @@ ayam_tracked = {}
 talenan_tracked = {}
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     run()
diff --git a/counter_live_rknn_bytetrack.py b/counter_live_rknn_bytetrack.py
index f905e17..1ad5e62 100644
--- a/counter_live_rknn_bytetrack.py
+++ b/counter_live_rknn_bytetrack.py
@@ -3,6 +3,7 @@ Edge production live counter — RTSP + YOLO RKNN + ByteTrack + line crossing.
 Runs on RK3588 hardware with RKNN model (320×320 input).
 Uses ByteTrack (Kalman filter + two-stage IoU association) for tracking.
 """
+
 import numpy as np
 import cv2
 import csv
@@ -13,74 +14,79 @@ from datetime import datetime
 from pathlib import Path
 
 from dotenv import load_dotenv
+
 load_dotenv()
 
 from rknnlite.api import RKNNLite
 from batch_store import BatchStore
 
 # --- config (override via env / .env) ---
-OUTPUT_DIR = os.getenv('OUTPUT_DIR', '/opt/jetson-counter')
-DB_PATH = os.getenv('DB_PATH', f'{OUTPUT_DIR}/jetson_counter.db')
-STATE_FILE = os.getenv('STATE_FILE', f'{OUTPUT_DIR}/current_batch.json')
-SOURCE = os.getenv('SOURCE', 'rtsp://user:pass@192.168.0.100:554/stream1')
-MODEL_PATH = os.getenv('MODEL_PATH', '/opt/jetson-counter/yolo11n.rknn')
-CAMERA_NAME = os.getenv('CAMERA_NAME', 'CC1')
-OBJECT_LABEL = os.getenv('OBJECT_LABEL', 'ayam-potong')
-CLASS_AYAM = os.getenv('CLASS_AYAM', 'ayam')
-CLASS_TALENAN = os.getenv('CLASS_TALENAN', 'talenan')
+OUTPUT_DIR = os.getenv("OUTPUT_DIR", "/opt/jetson-counter")
+DB_PATH = os.getenv("DB_PATH", f"{OUTPUT_DIR}/jetson_counter.db")
+STATE_FILE = os.getenv("STATE_FILE", f"{OUTPUT_DIR}/current_batch.json")
+SOURCE = os.getenv("SOURCE", "rtsp://user:pass@192.168.0.100:554/stream1")
+MODEL_PATH = os.getenv("MODEL_PATH", "/opt/jetson-counter/yolo11n.rknn")
+CAMERA_NAME = os.getenv("CAMERA_NAME", "CC1")
+OBJECT_LABEL = os.getenv("OBJECT_LABEL", "ayam-potong")
+CLASS_AYAM = os.getenv("CLASS_AYAM", "ayam")
+CLASS_TALENAN = os.getenv("CLASS_TALENAN", "talenan")
 
-LINE_X = int(os.getenv('LINE_X')) if os.getenv('LINE_X') else None
-LINE_X_FRAC = float(os.getenv('LINE_X_FRAC', '0.5'))
-CROSS_DIRECTION = os.getenv('CROSS_DIRECTION', 'rtl').lower()
+LINE_X = int(os.getenv("LINE_X")) if os.getenv("LINE_X") else None
+LINE_X_FRAC = float(os.getenv("LINE_X_FRAC", "0.5"))
+CROSS_DIRECTION = os.getenv("CROSS_DIRECTION", "rtl").lower()
 
-IMGSZ = int(os.getenv('IMGSZ', '320'))
-HALF = os.getenv('HALF', 'false').lower() == 'true'
-CONF = float(os.getenv('CONF', '0.3'))
-DEVICE = int(os.getenv('DEVICE', '0'))
+IMGSZ = int(os.getenv("IMGSZ", "320"))
+HALF = os.getenv("HALF", "false").lower() == "true"
+CONF = float(os.getenv("CONF", "0.3"))
+DEVICE = int(os.getenv("DEVICE", "0"))
 
 # RKNN NPU core mask
-CORE_MASK = int(os.getenv('CORE_MASK', '1'))
+CORE_MASK = int(os.getenv("CORE_MASK", "1"))
 
 # YOLO decoder config
-NUM_CLASSES = int(os.getenv('NUM_CLASSES', '2'))
-SCORE_SIGMOID = os.getenv('SCORE_SIGMOID', 'false').lower() == 'true'
+NUM_CLASSES = int(os.getenv("NUM_CLASSES", "2"))
+SCORE_SIGMOID = os.getenv("SCORE_SIGMOID", "false").lower() == "true"
 
 # ByteTrack settings
-TRACK_HIGH_THRESH = float(os.getenv('TRACK_HIGH_THRESH', '0.5'))
-TRACK_LOW_THRESH = float(os.getenv('TRACK_LOW_THRESH', '0.1'))
-TRACK_MATCH_THRESH = float(os.getenv('TRACK_MATCH_THRESH', '0.8'))
-TRACK_BUFFER = int(os.getenv('TRACK_BUFFER', '30'))
-TRACK_MIN_HITS = int(os.getenv('TRACK_MIN_HITS', '3'))
+TRACK_HIGH_THRESH = float(os.getenv("TRACK_HIGH_THRESH", "0.5"))
+TRACK_LOW_THRESH = float(os.getenv("TRACK_LOW_THRESH", "0.1"))
+TRACK_MATCH_THRESH = float(os.getenv("TRACK_MATCH_THRESH", "0.8"))
+TRACK_BUFFER = int(os.getenv("TRACK_BUFFER", "30"))
+TRACK_MIN_HITS = int(os.getenv("TRACK_MIN_HITS", "3"))
 
-DAILY_CUTOFF_TIME = os.getenv('DAILY_CUTOFF_TIME', '20:00')
-BATCH_TIMEOUT_SECONDS = float(os.getenv('BATCH_TIMEOUT_SECONDS', '300'))
-IGNORE_BATCH_LABEL_TIMEOUT = float(os.getenv('IGNORE_BATCH_LABEL_TIMEOUT_SECONDS', '30'))
-MIN_OBJECT_PER_BATCH = int(os.getenv('MIN_OBJECT_PER_BATCH', '60'))
-MIN_DURATION_PER_BATCH = int(os.getenv('MIN_DURATION_PER_BATCH', '60'))
+DAILY_CUTOFF_TIME = os.getenv("DAILY_CUTOFF_TIME", "20:00")
+BATCH_TIMEOUT_SECONDS = float(os.getenv("BATCH_TIMEOUT_SECONDS", "300"))
+IGNORE_BATCH_LABEL_TIMEOUT = float(
+    os.getenv("IGNORE_BATCH_LABEL_TIMEOUT_SECONDS", "30")
+)
+MIN_OBJECT_PER_BATCH = int(os.getenv("MIN_OBJECT_PER_BATCH", "60"))
+MIN_DURATION_PER_BATCH = int(os.getenv("MIN_DURATION_PER_BATCH", "60"))
 
-EXPORT_CSV = os.getenv('EXPORT_CSV', 'true').lower() == 'true'
-CROSS_CSV = os.getenv('CROSS_CSV', f'{OUTPUT_DIR}/batch_crossings.csv')
+EXPORT_CSV = os.getenv("EXPORT_CSV", "true").lower() == "true"
+CROSS_CSV = os.getenv("CROSS_CSV", f"{OUTPUT_DIR}/batch_crossings.csv")
 
-WARMUP_FRAMES = int(os.getenv('WARMUP_FRAMES', '30'))
-RECONNECT_DELAY_SEC = int(os.getenv('RECONNECT_DELAY_SEC', '3'))
-MAX_RECONNECT_ATTEMPTS = int(os.getenv('MAX_RECONNECT_ATTEMPTS', '0'))
-FLUSH_EVERY_N_FRAMES = int(os.getenv('FLUSH_EVERY_N_FRAMES', '100'))
-TRACKED_PRUNE_SEC = int(os.getenv('TRACKED_PRUNE_SEC', '300'))
-RECORD_VIDEO = os.getenv('RECORD_VIDEO', 'false').lower() == 'true'
-VIDEO_SEGMENT_SEC = int(os.getenv('VIDEO_SEGMENT_SEC', '3600'))
-OUTPUT_FPS = int(os.getenv('OUTPUT_FPS', '15'))
+WARMUP_FRAMES = int(os.getenv("WARMUP_FRAMES", "30"))
+RECONNECT_DELAY_SEC = int(os.getenv("RECONNECT_DELAY_SEC", "3"))
+MAX_RECONNECT_ATTEMPTS = int(os.getenv("MAX_RECONNECT_ATTEMPTS", "0"))
+FLUSH_EVERY_N_FRAMES = int(os.getenv("FLUSH_EVERY_N_FRAMES", "100"))
+TRACKED_PRUNE_SEC = int(os.getenv("TRACKED_PRUNE_SEC", "300"))
+RECORD_VIDEO = os.getenv("RECORD_VIDEO", "false").lower() == "true"
+VIDEO_SEGMENT_SEC = int(os.getenv("VIDEO_SEGMENT_SEC", "3600"))
+OUTPUT_FPS = int(os.getenv("OUTPUT_FPS", "15"))
 
-LIVE_STREAM_ENABLED = os.getenv('LIVE_STREAM_ENABLED', 'false').lower() == 'true'
-LIVE_STREAM_FRAME_PATH = os.getenv('LIVE_STREAM_FRAME_PATH', '/dev/shm/jetson-counter/live_frame.jpg')
-LIVE_STREAM_QUALITY = int(os.getenv('LIVE_STREAM_QUALITY', '75'))
-LIVE_STREAM_EVERY_N = int(os.getenv('LIVE_STREAM_EVERY_N', '2'))
+LIVE_STREAM_ENABLED = os.getenv("LIVE_STREAM_ENABLED", "false").lower() == "true"
+LIVE_STREAM_FRAME_PATH = os.getenv(
+    "LIVE_STREAM_FRAME_PATH", "/dev/shm/jetson-counter/live_frame.jpg"
+)
+LIVE_STREAM_QUALITY = int(os.getenv("LIVE_STREAM_QUALITY", "75"))
+LIVE_STREAM_EVERY_N = int(os.getenv("LIVE_STREAM_EVERY_N", "2"))
 
 RTSP_FFMPEG_OPTIONS = os.getenv(
-    'OPENCV_FFMPEG_CAPTURE_OPTIONS',
-    'rtsp_transport;tcp|fflags;nobuffer|flags;low_delay',
+    "OPENCV_FFMPEG_CAPTURE_OPTIONS",
+    "rtsp_transport;tcp|fflags;nobuffer|flags;low_delay",
 )
 
-IS_LIVE = SOURCE.lower().startswith(('rtsp://', 'http://'))
+IS_LIVE = SOURCE.lower().startswith(("rtsp://", "http://"))
 
 CROSS_FLASH_FRAMES = 12
 POPUP_LIFETIME = 20
@@ -90,8 +96,14 @@ BATCH_PULSE_FRAMES = 20
 
 SKELETON = [(0, 1), (4, 3), (1, 2), (3, 2), (2, 6), (2, 5), (2, 7), (7, 8)]
 SK_COLORS = [
-    (0, 255, 255), (0, 255, 255), (255, 0, 255), (255, 0, 255),
-    (0, 255, 0), (255, 255, 0), (0, 0, 255), (200, 200, 0),
+    (0, 255, 255),
+    (0, 255, 255),
+    (255, 0, 255),
+    (255, 0, 255),
+    (0, 255, 0),
+    (255, 255, 0),
+    (0, 0, 255),
+    (200, 200, 0),
 ]
 
 C_PANEL = (28, 24, 18)
@@ -111,7 +123,7 @@ shutdown_requested = False
 def request_shutdown(signum, frame):
     global shutdown_requested
     shutdown_requested = True
-    print('\nShutdown requested — finishing current frame...')
+    print("\nShutdown requested — finishing current frame...")
 
 
 signal.signal(signal.SIGINT, request_shutdown)
@@ -122,6 +134,7 @@ signal.signal(signal.SIGTERM, request_shutdown)
 # YOLO output decoder (NMS only — boxes are pre-decoded by the model)
 # =============================================================================
 
+
 def _nms(boxes, scores, iou_thr=0.45):
     order = np.argsort(scores)[::-1]
     keep = []
@@ -138,7 +151,9 @@ def _nms(boxes, scores, iou_thr=0.45):
         h = np.maximum(0.0, yy2 - yy1)
         inter = w * h
         area_i = (boxes[idx, 2] - boxes[idx, 0]) * (boxes[idx, 3] - boxes[idx, 1])
-        area_o = (boxes[order[1:], 2] - boxes[order[1:], 0]) * (boxes[order[1:], 3] - boxes[order[1:], 1])
+        area_o = (boxes[order[1:], 2] - boxes[order[1:], 0]) * (
+            boxes[order[1:], 3] - boxes[order[1:], 1]
+        )
         iou = inter / (area_i + area_o - inter + 1e-16)
         order = order[1:][iou < iou_thr]
     return np.array(keep)
@@ -148,6 +163,7 @@ def _nms(boxes, scores, iou_thr=0.45):
 # IoU helpers (xyxy format)
 # =============================================================================
 
+
 def _ious_xyxy(boxes_a, boxes_b):
     """Pairwise IoU: (N,4) vs (M,4) → (N,M) matrix."""
     n, m = len(boxes_a), len(boxes_b)
@@ -190,6 +206,7 @@ def _greedy_match(cost_matrix, threshold=0.3):
 # Kalman filter box tracker (state: x, y, w, h, vx, vy, vw, vh)
 # =============================================================================
 
+
 class KalmanBoxTracker:
     count = 0
 
@@ -242,6 +259,7 @@ class KalmanBoxTracker:
 
 class _KalmanFilter:
     """8-state constant-velocity Kalman filter for bounding box tracking."""
+
     def __init__(self):
         ndim, dt = 4, 1.0
         self.motion_mat = np.eye(2 * ndim, 2 * ndim, dtype=np.float32)
@@ -274,12 +292,16 @@ class _KalmanFilter:
         self.P = self.motion_mat @ self.P @ self.motion_mat.T + Q
 
     def update(self, z):
-        R = np.diag(np.square([
-            self._std_weight_position * z[2],
-            self._std_weight_position * z[3],
-            self._std_weight_position * z[2],
-            self._std_weight_position * z[3],
-        ]))
+        R = np.diag(
+            np.square(
+                [
+                    self._std_weight_position * z[2],
+                    self._std_weight_position * z[3],
+                    self._std_weight_position * z[2],
+                    self._std_weight_position * z[3],
+                ]
+            )
+        )
 
         H = self.update_mat
         S = H @ self.P @ H.T + R
@@ -295,11 +317,18 @@ class _KalmanFilter:
 # ByteTrack multi-object tracker
 # =============================================================================
 
+
 class ByteTracker:
     """ByteTrack: two-stage association with Kalman filter prediction."""
 
-    def __init__(self, track_high_thresh=0.5, track_low_thresh=0.1,
-                 match_thresh=0.8, track_buffer=30, min_hits=3):
+    def __init__(
+        self,
+        track_high_thresh=0.5,
+        track_low_thresh=0.1,
+        match_thresh=0.8,
+        track_buffer=30,
+        min_hits=3,
+    ):
         self.high_thresh = track_high_thresh
         self.low_thresh = track_low_thresh
         self.match_thresh = match_thresh
@@ -367,7 +396,9 @@ class ByteTracker:
                     tracked_map[track_pool[ti].track_id] = track_pool[ti].get_cx()
                     match_pairs_high.append((det_global, ti))
 
-            unmatched_tracks = [t for t in range(num_tracks) if t not in matched_track_idx]
+            unmatched_tracks = [
+                t for t in range(num_tracks) if t not in matched_track_idx
+            ]
 
             # --- second association: low-score ↔ unmatched tracks ---
             low_idx = np.where(is_low)[0]
@@ -383,10 +414,14 @@ class ByteTracker:
                     det_global = int(low_idx[di])
                     pool_idx = unmatched_tracks[uti]
                     track_pool[pool_idx].update(dets[det_global])
-                    track_pool[pool_idx].hit_streak = max(1, track_pool[pool_idx].hit_streak)
+                    track_pool[pool_idx].hit_streak = max(
+                        1, track_pool[pool_idx].hit_streak
+                    )
                     matched_track_idx.add(pool_idx)
                     det_to_track[det_global] = track_pool[pool_idx].track_id
-                    tracked_map[track_pool[pool_idx].track_id] = track_pool[pool_idx].get_cx()
+                    tracked_map[track_pool[pool_idx].track_id] = track_pool[
+                        pool_idx
+                    ].get_cx()
 
         # --- reset hit_streak for unmatched tracks ---
         for ti, trk in enumerate(track_pool):
@@ -432,9 +467,19 @@ class ByteTracker:
 # RKNN YOLO wrapper (detect output format: (1, 4+num_classes, N))
 # =============================================================================
 
+
 class RKNNYOLO:
-    def __init__(self, model_path, core_mask=1, imgsz=320, conf=0.3, iou=0.45,
-                 num_classes=2, num_keypoints=0, score_sigmoid=False):
+    def __init__(
+        self,
+        model_path,
+        core_mask=1,
+        imgsz=320,
+        conf=0.3,
+        iou=0.45,
+        num_classes=2,
+        num_keypoints=0,
+        score_sigmoid=False,
+    ):
         self.imgsz = imgsz
         self.conf = conf
         self.iou = iou
@@ -445,18 +490,18 @@ class RKNNYOLO:
         self.rknn = RKNNLite(verbose=False)
         ret = self.rknn.load_rknn(model_path)
         if ret != 0:
-            raise RuntimeError(f'Failed to load RKNN model: {model_path}')
+            raise RuntimeError(f"Failed to load RKNN model: {model_path}")
         ret = self.rknn.init_runtime(core_mask=core_mask)
         if ret != 0:
-            raise RuntimeError(f'Failed to init RKNN runtime (core_mask={core_mask})')
+            raise RuntimeError(f"Failed to init RKNN runtime (core_mask={core_mask})")
 
         try:
             sdk_ver = self.rknn.get_sdk_version()
-            print(f'RKNN SDK version: {sdk_ver}')
+            print(f"RKNN SDK version: {sdk_ver}")
         except Exception:
             pass
 
-        print(f'RKNN model loaded: {model_path}  imgsz={imgsz}  core_mask={core_mask}')
+        print(f"RKNN model loaded: {model_path}  imgsz={imgsz}  core_mask={core_mask}")
 
     def _preprocess(self, frame):
         h0, w0 = frame.shape[:2]
@@ -467,7 +512,7 @@ class RKNNYOLO:
         letterbox = np.full((self.imgsz, self.imgsz, 3), 114, dtype=np.uint8)
         dy = (self.imgsz - nh) // 2
         dx = (self.imgsz - nw) // 2
-        letterbox[dy:dy + nh, dx:dx + nw] = resized
+        letterbox[dy : dy + nh, dx : dx + nw] = resized
 
         rgb = cv2.cvtColor(letterbox, cv2.COLOR_BGR2RGB)
         gains = np.array([scale, scale, dy, dx], dtype=np.float32)
@@ -500,12 +545,15 @@ class RKNNYOLO:
         else:
             cls_scores = cls_raw
 
-        boxes_xyxy = np.stack([
-            boxes_cxcywh[:, 0] - boxes_cxcywh[:, 2] / 2,
-            boxes_cxcywh[:, 1] - boxes_cxcywh[:, 3] / 2,
-            boxes_cxcywh[:, 0] + boxes_cxcywh[:, 2] / 2,
-            boxes_cxcywh[:, 1] + boxes_cxcywh[:, 3] / 2,
-        ], axis=1)
+        boxes_xyxy = np.stack(
+            [
+                boxes_cxcywh[:, 0] - boxes_cxcywh[:, 2] / 2,
+                boxes_cxcywh[:, 1] - boxes_cxcywh[:, 3] / 2,
+                boxes_cxcywh[:, 0] + boxes_cxcywh[:, 2] / 2,
+                boxes_cxcywh[:, 1] + boxes_cxcywh[:, 3] / 2,
+            ],
+            axis=1,
+        )
 
         max_scores = cls_scores.max(axis=1)
         class_ids = cls_scores.argmax(axis=1)
@@ -536,12 +584,14 @@ class RKNNYOLO:
             keep = _nms(bboxes[idx], scores[idx], iou_thr=self.iou)
             for k in keep:
                 j = idx[k]
-                detections.append({
-                    'bbox': bboxes[j].tolist(),
-                    'score': float(scores[j]),
-                    'cls': int(clses[j]),
-                    'keypoints': None,
-                })
+                detections.append(
+                    {
+                        "bbox": bboxes[j].tolist(),
+                        "score": float(scores[j]),
+                        "cls": int(clses[j]),
+                        "keypoints": None,
+                    }
+                )
         return detections
 
     def release(self):
@@ -552,6 +602,7 @@ class RKNNYOLO:
 # Drawing helpers
 # =============================================================================
 
+
 def resolve_line_x(frame_width):
     if LINE_X is not None:
         return LINE_X
@@ -561,41 +612,41 @@ def resolve_line_x(frame_width):
 
 
 def crossed_line(prev_cx, cx, line_x, direction=CROSS_DIRECTION):
-    if direction == 'ltr':
+    if direction == "ltr":
         return prev_cx < line_x <= cx
-    if direction == 'both':
+    if direction == "both":
         return (prev_cx > line_x >= cx) or (prev_cx < line_x <= cx)
     return prev_cx > line_x >= cx
 
 
 def now_str():
-    return datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
 
 def open_capture(source):
-    if source.lower().startswith(('rtsp://', 'http://')):
-        os.environ['OPENCV_FFMPEG_CAPTURE_OPTIONS'] = RTSP_FFMPEG_OPTIONS
+    if source.lower().startswith(("rtsp://", "http://")):
+        os.environ["OPENCV_FFMPEG_CAPTURE_OPTIONS"] = RTSP_FFMPEG_OPTIONS
     cap = cv2.VideoCapture(source, cv2.CAP_FFMPEG)
     cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
     return cap
 
 
 def warmup_stream(cap, n=WARMUP_FRAMES):
-    print('Warming up stream...')
+    print("Warming up stream...")
     for _ in range(n):
         cap.read()
-    print('Stream ready!')
+    print("Stream ready!")
 
 
 def open_video_writer(path, w, h, fps):
-    return cv2.VideoWriter(path, cv2.VideoWriter_fourcc(*'avc1'), fps, (w, h))
+    return cv2.VideoWriter(path, cv2.VideoWriter_fourcc(*"avc1"), fps, (w, h))
 
 
 class CsvLogger:
     def __init__(self, path, header):
         Path(path).parent.mkdir(parents=True, exist_ok=True)
         new_file = not Path(path).exists() or Path(path).stat().st_size == 0
-        self.file = open(path, 'a', newline='', buffering=1)
+        self.file = open(path, "a", newline="", buffering=1)
         self.writer = csv.writer(self.file)
         if new_file:
             self.writer.writerow(header)
@@ -620,8 +671,8 @@ class VideoSegmentWriter:
         self._open_next()
 
     def _segment_path(self):
-        ts = datetime.now().strftime('%Y%m%d_%H%M%S')
-        return str(self.output_dir / f'live_{ts}.mp4')
+        ts = datetime.now().strftime("%Y%m%d_%H%M%S")
+        return str(self.output_dir / f"live_{ts}.mp4")
 
     def _open_next(self):
         if self.writer is not None:
@@ -629,7 +680,7 @@ class VideoSegmentWriter:
         path = self._segment_path()
         self.writer = open_video_writer(path, self.w, self.h, self.fps)
         self.segment_start = time.monotonic()
-        print(f'Recording segment: {path}')
+        print(f"Recording segment: {path}")
 
     def write(self, frame):
         if time.monotonic() - self.segment_start >= self.segment_sec:
@@ -642,7 +693,9 @@ class VideoSegmentWriter:
 
 
 def prune_stale_tracks(tracked, now_mono):
-    stale = [tid for tid, (_, ts) in tracked.items() if now_mono - ts > TRACKED_PRUNE_SEC]
+    stale = [
+        tid for tid, (_, ts) in tracked.items() if now_mono - ts > TRACKED_PRUNE_SEC
+    ]
     for tid in stale:
         del tracked[tid]
 
@@ -680,7 +733,16 @@ def draw_elegant_counting_line(img, line_x, h, pulse_remaining=0):
         y_end = min(y + dash_len, h)
         cv2.line(img, (line_x, y), (line_x, y_end), C_LINE_CORE, 2, cv2.LINE_AA)
         y += dash_len + gap
-    cv2.putText(img, 'COUNT LINE', (line_x - 46, 24), cv2.FONT_HERSHEY_SIMPLEX, 0.42, C_LINE_CORE, 1, cv2.LINE_AA)
+    cv2.putText(
+        img,
+        "COUNT LINE",
+        (line_x - 46, 24),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.42,
+        C_LINE_CORE,
+        1,
+        cv2.LINE_AA,
+    )
 
 
 def draw_hero_count(img, line_x, h, count, pulse_remaining=0):
@@ -691,34 +753,120 @@ def draw_hero_count(img, line_x, h, count, pulse_remaining=0):
     (tw, th), _ = cv2.getTextSize(text, font, font_scale, thickness)
     pad = 14
     tx, ty = line_x - tw // 2, h // 2 + th // 2
-    overlay_rect(img, tx - pad, ty - th - pad, tx + tw + pad, ty + pad // 2, C_PANEL, alpha=0.78)
-    cv2.rectangle(img, (tx - pad, ty - th - pad), (tx + tw + pad, ty + pad // 2), C_LINE_CORE, 2)
+    overlay_rect(
+        img, tx - pad, ty - th - pad, tx + tw + pad, ty + pad // 2, C_PANEL, alpha=0.78
+    )
+    cv2.rectangle(
+        img, (tx - pad, ty - th - pad), (tx + tw + pad, ty + pad // 2), C_LINE_CORE, 2
+    )
     cv2.putText(img, text, (tx, ty), font, font_scale, C_GREEN, thickness, cv2.LINE_AA)
 
 
-def draw_hud(img, w, batch_num, batch_count, total_ayam, elapsed_sec, rate, camera_id, clock):
+def draw_hud(
+    img, w, batch_num, batch_count, total_ayam, elapsed_sec, rate, camera_id, clock
+):
     bar_h = 52
     overlay_rect(img, 0, 0, w, bar_h, C_PANEL, alpha=0.72)
     cv2.line(img, (0, bar_h), (w, bar_h), C_BORDER, 1)
-    cv2.putText(img, 'BATCH', (16, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    batch_label = str(batch_num) if batch_num else '\u2014'
-    cv2.putText(img, batch_label, (16, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.9, C_ACCENT, 2, cv2.LINE_AA)
-    cv2.putText(img, 'COUNT', (100, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    cv2.putText(img, str(batch_count), (100, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.9, C_GREEN, 2, cv2.LINE_AA)
-    cv2.putText(img, 'TOTAL', (190, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    cv2.putText(img, str(total_ayam), (190, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.7, C_TEXT, 1, cv2.LINE_AA)
-    cv2.putText(img, 'UPTIME', (280, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    cv2.putText(img, f'{elapsed_sec / 3600:.1f}h', (280, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.7, C_TEXT, 1, cv2.LINE_AA)
-    cv2.putText(img, 'RATE', (380, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
-    cv2.putText(img, f'{rate:.1f}/min', (380, 44), cv2.FONT_HERSHEY_SIMPLEX, 0.7, C_ACCENT, 1, cv2.LINE_AA)
-    cv2.putText(img, clock, (w - 180, 36), cv2.FONT_HERSHEY_SIMPLEX, 0.55, C_TEXT, 1, cv2.LINE_AA)
-    cv2.putText(img, f'CAM {camera_id}', (w - 180, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
+    cv2.putText(
+        img, "BATCH", (16, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+    )
+    batch_label = str(batch_num) if batch_num else "\u2014"
+    cv2.putText(
+        img,
+        batch_label,
+        (16, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.9,
+        C_ACCENT,
+        2,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img, "COUNT", (100, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+    )
+    cv2.putText(
+        img,
+        str(batch_count),
+        (100, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.9,
+        C_GREEN,
+        2,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img, "TOTAL", (190, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+    )
+    cv2.putText(
+        img,
+        str(total_ayam),
+        (190, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.7,
+        C_TEXT,
+        1,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img,
+        "UPTIME",
+        (280, 20),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.45,
+        C_MUTED,
+        1,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img,
+        f"{elapsed_sec / 3600:.1f}h",
+        (280, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.7,
+        C_TEXT,
+        1,
+        cv2.LINE_AA,
+    )
+    cv2.putText(
+        img, "RATE", (380, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+    )
+    cv2.putText(
+        img,
+        f"{rate:.1f}/min",
+        (380, 44),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.7,
+        C_ACCENT,
+        1,
+        cv2.LINE_AA,
+    )
+    # cv2.putText(img, clock, (w - 180, 36), cv2.FONT_HERSHEY_SIMPLEX, 0.55, C_TEXT, 1, cv2.LINE_AA)
+    cv2.putText(
+        img,
+        f"CAM {camera_id}",
+        (w - 180, 20),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.45,
+        C_MUTED,
+        1,
+        cv2.LINE_AA,
+    )
 
 
 def draw_footer(img, w, h, frame_idx, live_tag):
     bar_h = 28
     overlay_rect(img, 0, h - bar_h, w, h, C_PANEL, alpha=0.55)
-    cv2.putText(img, f'{live_tag} | Frame {frame_idx}', (12, h - 9), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA)
+    cv2.putText(
+        img,
+        f"{live_tag} | Frame {frame_idx}",
+        (12, h - 9),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.45,
+        C_MUTED,
+        1,
+        cv2.LINE_AA,
+    )
 
 
 def draw_skeleton_bold(img, kpts):
@@ -738,28 +886,39 @@ def draw_skeleton_bold(img, kpts):
 def draw_popups(img, popups, frame_idx):
     alive = []
     for pop in popups:
-        age = frame_idx - pop['born']
+        age = frame_idx - pop["born"]
         if age > POPUP_LIFETIME:
             continue
         alive.append(pop)
         fade = 1.0 - age / POPUP_LIFETIME
-        y = pop['y'] - int(age * 1.8)
+        y = pop["y"] - int(age * 1.8)
         color = (int(C_GREEN[0] * fade), int(C_GREEN[1] * fade), int(C_GREEN[2] * fade))
-        cv2.putText(img, pop['text'], (pop['x'], y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, color, 2, cv2.LINE_AA)
+        cv2.putText(
+            img,
+            pop["text"],
+            (pop["x"], y),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            0.7,
+            color,
+            2,
+            cv2.LINE_AA,
+        )
     return alive
 
 
 def draw_batch_banner(img, w, batch_num, pulse_remaining):
     if pulse_remaining <= 0:
         return
-    text = f'NEW BATCH {batch_num}'
+    text = f"NEW BATCH {batch_num}"
     font = cv2.FONT_HERSHEY_SIMPLEX
     (tw, th), _ = cv2.getTextSize(text, font, 0.8, 2)
     x1, y1 = w // 2 - tw // 2 - 16, 62
     x2, y2 = w // 2 + tw // 2 + 16, 62 + th + 20
     overlay_rect(img, x1, y1, x2, y2, C_PANEL, alpha=0.7)
     cv2.rectangle(img, (x1, y1), (x2, y2), C_ACCENT, 2)
-    cv2.putText(img, text, (w // 2 - tw // 2, 62 + th + 4), font, 0.8, C_ACCENT, 2, cv2.LINE_AA)
+    cv2.putText(
+        img, text, (w // 2 - tw // 2, 62 + th + 4), font, 0.8, C_ACCENT, 2, cv2.LINE_AA
+    )
 
 
 def connect_stream(source, warmup=WARMUP_FRAMES):
@@ -769,11 +928,13 @@ def connect_stream(source, warmup=WARMUP_FRAMES):
         if not cap.isOpened():
             attempts += 1
             if MAX_RECONNECT_ATTEMPTS and attempts >= MAX_RECONNECT_ATTEMPTS:
-                raise RuntimeError(f'Cannot open source after {attempts} attempts: {source}')
-            print(f'Cannot open source, retry in {RECONNECT_DELAY_SEC}s...')
+                raise RuntimeError(
+                    f"Cannot open source after {attempts} attempts: {source}"
+                )
+            print(f"Cannot open source, retry in {RECONNECT_DELAY_SEC}s...")
             time.sleep(RECONNECT_DELAY_SEC)
             continue
-        if warmup > 0 and source.lower().startswith(('rtsp://', 'http://')):
+        if warmup > 0 and source.lower().startswith(("rtsp://", "http://")):
             warmup_stream(cap, warmup)
         w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
         h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
@@ -788,6 +949,7 @@ def connect_stream(source, warmup=WARMUP_FRAMES):
 # Main loop
 # =============================================================================
 
+
 def run():
     global shutdown_requested
 
@@ -801,13 +963,15 @@ def run():
         ignore_batch_label_timeout=IGNORE_BATCH_LABEL_TIMEOUT,
         min_object_per_batch=MIN_OBJECT_PER_BATCH,
         min_duration_per_batch=MIN_DURATION_PER_BATCH,
-        logger=lambda msg: print(f'[{now_str()}] {msg}'),
+        logger=lambda msg: print(f"[{now_str()}] {msg}"),
     )
     store.start_cutoff_watcher()
 
     cross_logger = None
     if EXPORT_CSV:
-        cross_logger = CsvLogger(CROSS_CSV, ['batch', 'frame', 'timestamp', 'chicken_id'])
+        cross_logger = CsvLogger(
+            CROSS_CSV, ["batch", "frame", "timestamp", "chicken_id"]
+        )
 
     model = RKNNYOLO(
         model_path=MODEL_PATH,
@@ -819,8 +983,8 @@ def run():
     )
 
     CLASS_IDS = {
-        os.getenv('CLASS_AYAM', 'ayam'): 0,
-        os.getenv('CLASS_TALENAN', 'talenan'): 1,
+        os.getenv("CLASS_AYAM", "ayam"): 0,
+        os.getenv("CLASS_TALENAN", "talenan"): 1,
     }
     ayam_cls = CLASS_IDS[CLASS_AYAM]
     talenan_cls = CLASS_IDS[CLASS_TALENAN]
@@ -859,12 +1023,16 @@ def run():
         return
 
     line_x = resolve_line_x(w)
-    print(f'RKNN+ByteTrack counter | {w}x{h} @ {fps}fps | line x={line_x} | cross={CROSS_DIRECTION}')
-    print(f'Model: {MODEL_PATH} | imgsz={IMGSZ} | core_mask={CORE_MASK}')
-    print(f'ByteTrack: high_thresh={TRACK_HIGH_THRESH} low_thresh={TRACK_LOW_THRESH} '
-          f'match_thresh={TRACK_MATCH_THRESH} buffer={TRACK_BUFFER}')
-    print(f'DB: {DB_PATH}')
-    print(f'State: {STATE_FILE}')
+    print(
+        f"RKNN+ByteTrack counter | {w}x{h} @ {fps}fps | line x={line_x} | cross={CROSS_DIRECTION}"
+    )
+    print(f"Model: {MODEL_PATH} | imgsz={IMGSZ} | core_mask={CORE_MASK}")
+    print(
+        f"ByteTrack: high_thresh={TRACK_HIGH_THRESH} low_thresh={TRACK_LOW_THRESH} "
+        f"match_thresh={TRACK_MATCH_THRESH} buffer={TRACK_BUFFER}"
+    )
+    print(f"DB: {DB_PATH}")
+    print(f"State: {STATE_FILE}")
 
     if RECORD_VIDEO:
         video_writer = VideoSegmentWriter(OUTPUT_DIR, w, h, fps, VIDEO_SEGMENT_SEC)
@@ -877,7 +1045,9 @@ def run():
             if not IS_LIVE:
                 break
             reconnect_count += 1
-            print(f'Stream dropped (attempt {reconnect_count}), reconnecting in {RECONNECT_DELAY_SEC}s...')
+            print(
+                f"Stream dropped (attempt {reconnect_count}), reconnecting in {RECONNECT_DELAY_SEC}s..."
+            )
             cap.release()
             time.sleep(RECONNECT_DELAY_SEC)
             cap, w, h, fps = connect_stream(SOURCE)
@@ -905,10 +1075,10 @@ def run():
             talenan_cx_list = []
 
             for det in detections:
-                bbox = det['bbox']
-                score = det['score']
-                cls_id = det['cls']
-                kpts = det['keypoints']
+                bbox = det["bbox"]
+                score = det["score"]
+                cls_id = det["cls"]
+                kpts = det["keypoints"]
                 cx = (bbox[0] + bbox[2]) / 2.0
 
                 if cls_id == talenan_cls:
@@ -928,9 +1098,11 @@ def run():
             talenan_scores = np.array(talenan_scores, dtype=np.float32)
 
             ayam_track_map, ayam_det_to_track, ayam_lost_map = ayam_tracker.update(
-                ayam_boxes_xyxy, ayam_scores)
-            talenan_track_map, talenan_det_to_track, talenan_lost_map = talenan_tracker.update(
-                talenan_boxes_xyxy, talenan_scores)
+                ayam_boxes_xyxy, ayam_scores
+            )
+            talenan_track_map, talenan_det_to_track, talenan_lost_map = (
+                talenan_tracker.update(talenan_boxes_xyxy, talenan_scores)
+            )
 
             # Process talenan crossings
             for di in range(len(talenan_boxes_xyxy)):
@@ -942,17 +1114,22 @@ def run():
 
                 if tid in talenan_tracked:
                     prev_cx = talenan_tracked[tid][0]
-                    if crossed_line(prev_cx, cx, line_x) and tid not in talenan_line_crossed:
+                    if (
+                        crossed_line(prev_cx, cx, line_x)
+                        and tid not in talenan_line_crossed
+                    ):
                         talenan_line_crossed.add(tid)
                         if store.record_talenan_crossing(tid):
                             batch_closed_frame = True
                             talenan_cross_flash[tid] = CROSS_FLASH_FRAMES
-                            popups.append({
-                                'x': int(cx) - 20,
-                                'y': int((bbox[1] + bbox[3]) / 2),
-                                'born': frame_idx,
-                                'text': 'BATCH CLOSED',
-                            })
+                            popups.append(
+                                {
+                                    "x": int(cx) - 20,
+                                    "y": int((bbox[1] + bbox[3]) / 2),
+                                    "born": frame_idx,
+                                    "text": "BATCH CLOSED",
+                                }
+                            )
                 talenan_tracked[tid] = (cx, mono)
 
             # Process ayam crossings (including lost tracks for line-cross continuity)
@@ -964,24 +1141,36 @@ def run():
 
                 if tid in ayam_tracked:
                     prev_cx = ayam_tracked[tid][0]
-                    if crossed_line(prev_cx, cx, line_x) and tid not in ayam_line_crossed:
+                    if (
+                        crossed_line(prev_cx, cx, line_x)
+                        and tid not in ayam_line_crossed
+                    ):
                         ayam_line_crossed.add(tid)
                         _, started_new = store.record_ayam_crossing(tid)
                         if cross_logger:
-                            cross_logger.write_row([
-                                store.current_batch_number, frame_idx,
-                                datetime.now().isoformat(), tid,
-                            ])
+                            cross_logger.write_row(
+                                [
+                                    store.current_batch_number,
+                                    frame_idx,
+                                    datetime.now().isoformat(),
+                                    tid,
+                                ]
+                            )
                         ayam_crossed_frame = True
                         if started_new:
                             batch_started_frame = True
                         ayam_cross_flash[tid] = CROSS_FLASH_FRAMES
-                        popups.append({
-                            'x': int(cx) - 12,
-                            'y': int((ayam_boxes_xyxy[di][1] + ayam_boxes_xyxy[di][3]) / 2),
-                            'born': frame_idx,
-                            'text': '+1',
-                        })
+                        popups.append(
+                            {
+                                "x": int(cx) - 12,
+                                "y": int(
+                                    (ayam_boxes_xyxy[di][1] + ayam_boxes_xyxy[di][3])
+                                    / 2
+                                ),
+                                "born": frame_idx,
+                                "text": "+1",
+                            }
+                        )
                 ayam_tracked[tid] = (cx, mono)
 
             # Also track lost tracks for line-crossing continuity
@@ -999,7 +1188,7 @@ def run():
                 flash = talenan_cross_flash.get(tid, 0)
                 color = C_GREEN if flash > 0 else C_TALENAN_BOX
                 cv2.rectangle(frame, (x1, y1), (x2, y2), color, 3 if flash > 0 else 2)
-                draw_pill(frame, f'TALENAN {tid}', x1, y1 - 4, color)
+                draw_pill(frame, f"TALENAN {tid}", x1, y1 - 4, color)
 
             # Draw ayam
             for di in range(len(ayam_boxes_xyxy)):
@@ -1011,7 +1200,7 @@ def run():
                 flash = ayam_cross_flash.get(tid, 0)
                 color = C_GREEN if flash > 0 else C_AYAM_BOX
                 cv2.rectangle(frame, (x1, y1), (x2, y2), color, 3 if flash > 0 else 2)
-                draw_pill(frame, f'ID {tid}', x1, y1 - 4, color)
+                draw_pill(frame, f"ID {tid}", x1, y1 - 4, color)
                 kpts = ayam_kpts_list[di] if di < len(ayam_kpts_list) else None
                 if kpts is not None:
                     draw_skeleton_bold(frame, kpts)
@@ -1031,9 +1220,21 @@ def run():
 
         draw_elegant_counting_line(frame, line_x, h, line_pulse)
         draw_hero_count(frame, line_x, h, batch_count, count_pulse)
-        draw_hud(frame, w, batch_num, batch_count, display_total, elapsed, rate, CAMERA_NAME, now_str())
+        draw_hud(
+            frame,
+            w,
+            batch_num,
+            batch_count,
+            display_total,
+            elapsed,
+            rate,
+            CAMERA_NAME,
+            now_str(),
+        )
         draw_batch_banner(frame, w, batch_num, batch_pulse)
-        draw_footer(frame, w, h, frame_idx, 'LIVE-RKNN-BT' if IS_LIVE else 'FILE-RKNN-BT')
+        draw_footer(
+            frame, w, h, frame_idx, "LIVE-RKNN-BT" if IS_LIVE else "FILE-RKNN-BT"
+        )
         popups = draw_popups(frame, popups, frame_idx)
 
         for flash_store in (ayam_cross_flash, talenan_cross_flash):
@@ -1051,8 +1252,10 @@ def run():
         if LIVE_STREAM_ENABLED and frame_idx % LIVE_STREAM_EVERY_N == 0:
             try:
                 Path(LIVE_STREAM_FRAME_PATH).parent.mkdir(parents=True, exist_ok=True)
-                _, jpeg = cv2.imencode('.jpg', frame, [cv2.IMWRITE_JPEG_QUALITY, LIVE_STREAM_QUALITY])
-                with open(LIVE_STREAM_FRAME_PATH, 'wb') as f:
+                _, jpeg = cv2.imencode(
+                    ".jpg", frame, [cv2.IMWRITE_JPEG_QUALITY, LIVE_STREAM_QUALITY]
+                )
+                with open(LIVE_STREAM_FRAME_PATH, "wb") as f:
                     f.write(jpeg.tobytes())
             except Exception:
                 pass
@@ -1060,8 +1263,8 @@ def run():
         frame_idx += 1
         if frame_idx % FLUSH_EVERY_N_FRAMES == 0:
             print(
-                f'[{now_str()}] Frame {frame_idx} | Batch {batch_num}: {batch_count} '
-                f'| Total: {display_total} | Uptime {elapsed / 3600:.2f}h'
+                f"[{now_str()}] Frame {frame_idx} | Batch {batch_num}: {batch_count} "
+                f"| Total: {display_total} | Uptime {elapsed / 3600:.2f}h"
             )
         prune_stale_tracks(ayam_tracked, mono)
         prune_stale_tracks(talenan_tracked, mono)
@@ -1074,13 +1277,13 @@ def run():
     model.release()
     store.shutdown()
 
-    print('\n=== Batch Summary (SQLite) ===')
-    print(f'Database: {DB_PATH}')
+    print("\n=== Batch Summary (SQLite) ===")
+    print(f"Database: {DB_PATH}")
 
 
 ayam_tracked = {}
 talenan_tracked = {}
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     run()