Latest Leveling with python Fix!

.env

@@ -1,17 +1,20 @@
 # Edge RK3588 production counter — copy to .env on device
-# cp .env.example .env && nano .env
+# cp config.env.example .env && nano .env
 
-OUTPUT_DIR=/opt/bytetrack-counter-cpp
-DB_PATH=/opt/bytetrack-counter-cpp/bytetrack_counter.db
+#DEBUG_TRACKING=true
+SITE_NAME=Salatiga
+
+OUTPUT_DIR=/opt/bytetrack-counter
+DB_PATH=/opt/bytetrack-counter/bytetrack_counter.db
 STATE_FILE=/tmp/bytetrack_current_batch.json
 
 # Direct LAN camera RTSP (low latency)
-#SOURCE=rtsp://frigate:zenai@192.168.192.16:8554/camera_stream_640
-SOURCE=rtsp://192.168.192.53:8554/my_stream
+#SOURCE=rtsp://frigate:zenai@127.0.0.1:8554/camera_stream_640
+SOURCE=rtsp://10.38.30.64:8554/my_stream
 OPENCV_FFMPEG_CAPTURE_OPTIONS=rtsp_transport;tcp|fflags;nobuffer|flags;low_delay
 
-# RKNN model — export'd from YOLO with imgsz=320
-MODEL_PATH=/opt/models/zenai_apc_cicalengka_20260609.rknn
+# RKNN model — export'd from YOLO9t with imgsz=320
+MODEL_PATH=/opt/models/zenai_apc_salatiga_20260703.rknn
 IMGSZ=320
 HALF=false
 CONF=0.3
@@ -21,24 +24,31 @@ CORE_MASK=7
 
 # YOLO decoder params (must match model export)
 NUM_CLASSES=2
-SCORE_SIGMOID=false
+NUM_KEYPOINTS=9
+REG_MAX=16
+STRIDES=8,16,32
 
-CAMERA_NAME=CC1
+CAMERA_NAME=ZenAi
 OBJECT_LABEL=ayam-potong
 CLASS_AYAM=ayam
-CLASS_TALENAN=telenan
+CLASS_TALENAN=talenan
 
 # Line crossing: rtl (default) | ltr | both
-CROSS_DIRECTION=ltr
+CROSS_DIRECTION=rtl
 LINE_X=
 LINE_X_FRAC=0.5
 
-DAILY_CUTOFF_TIME=17:00
+DAILY_CUTOFF_TIME=20:00
+CUTOFF_TIME=20:00
 BATCH_TIMEOUT_SECONDS=300
 IGNORE_BATCH_LABEL_TIMEOUT_SECONDS=30
 MIN_OBJECT_PER_BATCH=60
 MIN_DURATION_PER_BATCH=60
 
+DASHBOARD_HOST=0.0.0.0
+DASHBOARD_PORT=5001
+SECRET_KEY=change-me-in-production
+
 EXPORT_CSV=true
 RECORD_VIDEO=false
 
@@ -47,6 +57,14 @@ LIVE_STREAM_FRAME_PATH=/dev/shm/bytetrack-counter/live_frame.jpg
 LIVE_STREAM_QUALITY=75
 LIVE_STREAM_EVERY_N=2
 
-LOG_LEVEL=info
+# Lower high_thresh to match CONF so all valid detections create tracks
+TRACK_HIGH_THRESH_0=0.3
+TRACK_HIGH_THRESH_1=0.3
 
-DASHBOARD_PORT=5001
+# Relax match_thresh for ayam (0.8 is too strict, IoU must be > 0.8 to keep identity)
+TRACK_MATCH_THRESH_0=0.5
+TRACK_MATCH_THRESH_1=0.5
+
+# Lower low_thresh below CONF so filtering doesn't interfere
+TRACK_LOW_THRESH_0=0.1
+TRACK_LOW_THRESH_1=0.1

CMakeLists.txt

@@ -10,7 +10,7 @@ set(Eigen3_DIR /usr/share/eigen3/cmake)
 find_package(Eigen3 REQUIRED NO_MODULE)
 find_package(SQLite3 REQUIRED)
 
-option(HAS_RKNN "Build with RKNN NPU support" OFF)
+option(HAS_RKNN "Build with RKNN NPU support" ON)
 
 if(HAS_RKNN)
     add_definitions(-DHAS_RKNN)

RUN.md

@@ -0,0 +1,74 @@
+# ByteTrack Counter C++ — How to Run
+
+## Build
+
+```bash
+cd /opt/bytetrack-counter-cpp
+mkdir -p build && cd build
+cmake .. -DHAS_RKNN=ON
+make -j$(nproc)
+```
+
+## Run
+
+Run from the project root (looks for `.env` in CWD by default):
+
+```bash
+cd /opt/bytetrack-counter-cpp
+./build/bytetrack-counter
+```
+
+### Specify a custom env file
+
+Pass the path as the first argument:
+
+```bash
+./build/bytetrack-counter /path/to/custom.env
+```
+
+Or via environment variable:
+
+```bash
+ENV_FILE=/path/to/custom.env ./build/bytetrack-counter
+```
+
+### Priority
+
+1. CLI argument (if provided)
+2. `ENV_FILE` environment variable (if set)
+3. `./.env` in the working directory
+
+## Service (systemd)
+
+```bash
+sudo systemctl restart bytetrack-counter
+journalctl -u bytetrack-counter -f
+```
+
+## Environment Variables
+
+See `.env.example` for a full reference. Key variables:
+
+| Variable | Default | Description |
+|---|---|---|
+| `SOURCE` | `rtsp://user:pass@192.168.0.100:554/stream1` | RTSP camera URL |
+| `MODEL_PATH` | `/opt/models/yolo.rknn` | RKNN model file |
+| `IMGSZ` | `320` | Model input size |
+| `CONF` | `0.3` | Detection confidence threshold |
+| `CORE_MASK` | `1` | RKNN NPU core mask (1, 2, 3, 7) |
+| `CAMERA_NAME` | `CC1` | Camera ID label |
+| `CROSS_DIRECTION` | `rtl` | Line crossing direction: `rtl`, `ltr`, `both` |
+| `LINE_X_FRAC` | `0.5` | Counting line position (fraction of frame width) |
+| `TRACK_HIGH_THRESH_0` | `0.5` | ByteTrack high threshold (ayam) |
+| `TRACK_MATCH_THRESH_0` | `0.8` | ByteTrack match threshold (ayam) |
+| `TRACK_HIGH_THRESH_1` | `0.5` | ByteTrack high threshold (talenan) |
+| `TRACK_MATCH_THRESH_1` | `0.6` | ByteTrack match threshold (talenan) |
+| `AYAM_CLASS_ID` | `0` | YOLO class ID for ayam |
+| `TALENAN_CLASS_ID` | `1` | YOLO class ID for talenan |
+| `RATE_WINDOW_SEC` | `60` | Rate calculation sliding window (seconds) |
+| `RECONNECT_DELAY_SEC` | `3` | Reconnect delay on stream drop / initial connect |
+| `MAX_RECONNECT_ATTEMPTS` | `0` | Max reconnect attempts (0 = unlimited) |
+| `LIVE_STREAM_ENABLED` | `false` | Write JPEG snapshot for web dashboard |
+| `RECORD_VIDEO` | `false` | Record MP4 video segments |
+| `OUTPUT_DIR` | `/opt/bytetrack-counter-cpp` | Data output directory |
+| `DB_PATH` | `{OUTPUT_DIR}/bytetrack_counter.db` | SQLite database path |

config.env.example

@@ -0,0 +1,152 @@
+# =============================================================================
+# Edge RK3588 production counter + dashboard
+# Shared config for: counter_live_rknn_bytetrack.py + counter_dashboard.py
+# Copy to .env on device:  cp config.env.example .env && nano .env
+# =============================================================================
+
+# --- Core paths ---
+# Root output directory (logs, DB, video, CSV)
+OUTPUT_DIR=/opt/bytetrack-counter
+# SQLite database path for batch entries & crossing logs
+DB_PATH=/opt/bytetrack-counter/bytetrack_counter.db
+# JSON file persisting the current active batch state
+STATE_FILE=/tmp/bytetrack_current_batch.json
+
+# --- Input source ---
+# RTSP / HTTP live stream, or a local video file path
+SOURCE=rtsp://user:pass@192.168.0.100:554/stream1
+# FFmpeg capture options passed to cv2.VideoCapture (RTSP low-latency flags)
+OPENCV_FFMPEG_CAPTURE_OPTIONS=rtsp_transport;tcp|fflags;nobuffer|flags;low_delay
+
+# --- RKNN model ---
+# Path to exported .rknn model (YOLO format, e.g. yolo11n.rknn)
+MODEL_PATH=/opt/models/yolo9t.rknn
+# Input image size for the model (square, e.g. 320 → 320×320)
+IMGSZ=320
+# Use FP16 inference on NPU (true/false); currently unused in ByteTrack variant
+HALF=false
+# NPU core mask: 1=core0, 2=core1, 3=core0+core1, 7=all three
+CORE_MASK=7
+# Compute device index (reserved; not used at runtime)
+DEVICE=0
+
+# --- YOLO decoder ---
+# Number of object classes the model outputs (e.g. 2 = ayam + talenan)
+NUM_CLASSES=2
+# Apply sigmoid to raw class scores (true/false); set true if model head uses BCE logits
+SCORE_SIGMOID=false
+
+# --- Detection ---
+# Confidence threshold – detections below this are discarded before NMS
+CONF=0.3
+
+# --- ByteTrack tracking ---
+# General for ayam, index 0
+# Detections with score ≥ this get priority matching in the first association stage
+TRACK_HIGH_THRESH_0=0.5
+# Detections with score between this and TRACK_HIGH_THRESH are matched in the second stage
+TRACK_LOW_THRESH_0=0.1
+# IoU threshold for the first-stage association (0–1). Higher = stricter overlap required
+TRACK_MATCH_THRESH_0=0.8
+# Frames a track survives without a match before being permanently removed
+TRACK_BUFFER_0=30
+# Minimum consecutive (or total) hits needed before a track is considered confirmed
+TRACK_MIN_HITS_0=3
+
+# For talenan, index 1
+# Detections with score ≥ this get priority matching in the first association stage
+TRACK_HIGH_THRESH_1=0.5
+# Detections with score between this and TRACK_HIGH_THRESH are matched in the second stage
+TRACK_LOW_THRESH_1=0.1
+# IoU threshold for the first-stage association (0–1). Higher = stricter overlap required
+TRACK_MATCH_THRESH_1=0.6
+# Frames a track survives without a match before being permanently removed
+TRACK_BUFFER_1=30
+# Minimum consecutive (or total) hits needed before a track is considered confirmed
+TRACK_MIN_HITS_1=3
+
+# --- Display ---
+# Site name shown on the dashboard header (top-right)
+SITE_NAME=ZenAi
+
+# --- Object class names ---
+# Camera / location identifier shown in HUD and stored in DB
+CAMERA_NAME=ZenAi
+# Label used for batch grouping in the database
+OBJECT_LABEL=ayam-potong
+# Class name for the counted object (must match NUM_CLASSES order, index 0)
+CLASS_AYAM=ayam
+# Class name for the batch-closing trigger object (must match NUM_CLASSES order, index 1)
+CLASS_TALENAN=talenan
+
+# --- Line crossing ---
+# Direction for counting: rtl (right-to-left, default) | ltr (left-to-right) | both
+CROSS_DIRECTION=rtl
+# Fixed x-coordinate for the counting line (overrides LINE_X_FRAC if set)
+LINE_X=
+# Fraction of frame width where the counting line is drawn (default 0.5 = centre)
+LINE_X_FRAC=0.5
+
+# --- Batch management ---
+# Daily cutoff time (HH:MM) – a new day's batch numbering starts after this time.
+# CUTOFF_TIME is an alias used by the dashboard; DAILY_CUTOFF_TIME takes priority in counter_live_rknn_bytetrack.py.
+DAILY_CUTOFF_TIME=20:00
+CUTOFF_TIME=20:00
+# Seconds of inactivity after which the current batch is auto-closed
+BATCH_TIMEOUT_SECONDS=300
+# Seconds a newly-opened batch ignores the talenan label before accepting a close trigger
+IGNORE_BATCH_LABEL_TIMEOUT_SECONDS=30
+# Minimum number of objects required for a batch to be saved as valid
+MIN_OBJECT_PER_BATCH=60
+# Minimum duration in seconds a batch must be open to be saved as valid
+MIN_DURATION_PER_BATCH=60
+
+# --- CSV export ---
+# Write per-crossing events to a CSV file (true/false)
+EXPORT_CSV=true
+# Path where the crossing CSV is written
+CROSS_CSV=/opt/batch-counter/batch_crossings.csv
+
+# --- Rate / performance ---
+# Sliding window in seconds for computing the crossing rate (objects/minute)
+RATE_WINDOW_SEC=60
+# Number of frames to discard at startup to let the stream buffer stabilise
+WARMUP_FRAMES=30
+# Delay in seconds between stream reconnection attempts
+RECONNECT_DELAY_SEC=3
+# Maximum reconnection attempts (0 = infinite)
+MAX_RECONNECT_ATTEMPTS=0
+# Print status log every N processed frames
+FLUSH_EVERY_N_FRAMES=100
+# Seconds after which a tracked but unseen object is pruned from the active set
+TRACKED_PRUNE_SEC=300
+
+# --- Video recording ---
+# Save annotated frames to segmented MP4 files (true/false)
+RECORD_VIDEO=false
+# Duration in seconds of each video segment file
+VIDEO_SEGMENT_SEC=3600
+# Output video FPS (fallback if source FPS is unknown or ≤ 1)
+OUTPUT_FPS=15
+
+# --- Live stream snapshot ---
+# Periodically write the latest annotated frame as JPEG for an external web server
+LIVE_STREAM_ENABLED=false
+# Path to the shared-memory snapshot file (served by nginx / lighttpd)
+LIVE_STREAM_FRAME_PATH=/dev/shm/byetrack-counter/live_frame.jpg
+# JPEG quality (1–100)
+LIVE_STREAM_QUALITY=75
+# Write the snapshot every N frames (lower = more frequent updates)
+LIVE_STREAM_EVERY_N=2
+
+# --- Dashboard (counter_dashboard.py) ---
+# Flask secret key for session/cookie signing — change in production!
+SECRET_KEY=change-me-in-production
+# Bind address for the Flask web server
+DASHBOARD_HOST=0.0.0.0
+# Listen port for the dashboard web UI
+DASHBOARD_PORT=5000
+# Enable Flask debug mode (true/false) — auto-reloads on code changes; disable in production
+FLASK_DEBUG=false
+# Fallback name for the active-batch JSON state file used by the dashboard
+CURRENT_BATCH_PATH=/tmp/bytetrack_current_batch.json

counter_live_rknn_bytetrack.py

@@ -10,6 +10,7 @@ import csv
 import os
 import signal
 import time
+from collections import deque
 from datetime import datetime
 from pathlib import Path
 
@@ -48,11 +49,18 @@ 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"))
+# Ayam index 0
+TRACK_HIGH_THRESH_0 = float(os.getenv("TRACK_HIGH_THRESH_0", "0.5"))
+TRACK_LOW_THRESH_0 = float(os.getenv("TRACK_LOW_THRESH_0", "0.1"))
+TRACK_MATCH_THRESH_0 = float(os.getenv("TRACK_MATCH_THRESH_0", "0.8"))
+TRACK_BUFFER_0 = int(os.getenv("TRACK_BUFFER_0", "30"))
+TRACK_MIN_HITS_0 = int(os.getenv("TRACK_MIN_HITS_0", "3"))
+# Talenan index 1
+TRACK_HIGH_THRESH_1 = float(os.getenv("TRACK_HIGH_THRESH_1", "0.5"))
+TRACK_LOW_THRESH_1 = float(os.getenv("TRACK_LOW_THRESH_1", "0.1"))
+TRACK_MATCH_THRESH_1 = float(os.getenv("TRACK_MATCH_THRESH_1", "0.6"))
+TRACK_BUFFER_1 = int(os.getenv("TRACK_BUFFER_1", "30"))
+TRACK_MIN_HITS_1 = int(os.getenv("TRACK_MIN_HITS_1", "3"))
 
 DAILY_CUTOFF_TIME = os.getenv("DAILY_CUTOFF_TIME", "20:00")
 BATCH_TIMEOUT_SECONDS = float(os.getenv("BATCH_TIMEOUT_SECONDS", "300"))
@@ -65,6 +73,7 @@ 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")
 
+RATE_WINDOW_SEC = int(os.getenv("RATE_WINDOW_SEC", "60"))
 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"))
@@ -345,11 +354,13 @@ class ByteTracker:
         # --- separate detections by score ---
         if len(boxes_xyxy) > 0:
             remain = scores > self.low_thresh
+            remain_orig_idx = np.where(remain)[0]
             dets = boxes_xyxy[remain]
             det_scores = scores[remain]
             is_high = det_scores > self.high_thresh
             is_low = ~is_high
         else:
+            remain_orig_idx = np.zeros(0, dtype=np.int64)
             dets = np.zeros((0, 4), dtype=np.float32)
             det_scores = np.zeros(0, dtype=np.float32)
             is_high = np.zeros(0, dtype=bool)
@@ -389,10 +400,11 @@ class ByteTracker:
 
                 for di, ti in matches:
                     det_global = int(high_idx[di])
+                    orig_idx = int(remain_orig_idx[det_global])
                     track_pool[ti].update(dets[det_global])
                     track_pool[ti].hit_streak = max(1, track_pool[ti].hit_streak)
                     matched_track_idx.add(ti)
-                    det_to_track[det_global] = track_pool[ti].track_id
+                    det_to_track[orig_idx] = track_pool[ti].track_id
                     tracked_map[track_pool[ti].track_id] = track_pool[ti].get_cx()
                     match_pairs_high.append((det_global, ti))
 
@@ -408,17 +420,20 @@ class ByteTracker:
                 unmatched_boxes = track_boxes[unmatched_tracks]
                 iou_mat = _ious_xyxy(low_dets, unmatched_boxes)
                 cost_mat = 1.0 - iou_mat
-                matches2 = _greedy_match(cost_mat, threshold=0.5)
+                matches2 = _greedy_match(
+                    cost_mat, threshold=1.0 - self.match_thresh
+                )
 
                 for di, uti in matches2:
                     det_global = int(low_idx[di])
                     pool_idx = unmatched_tracks[uti]
+                    orig_idx = int(remain_orig_idx[det_global])
                     track_pool[pool_idx].update(dets[det_global])
                     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
+                    det_to_track[orig_idx] = track_pool[pool_idx].track_id
                     tracked_map[track_pool[pool_idx].track_id] = track_pool[
                         pool_idx
                     ].get_cx()
@@ -454,10 +469,11 @@ class ByteTracker:
         high_all = np.where(is_high)[0]
         matched_det_ids = set(det_to_track.keys())
         for dg in high_all:
-            if int(dg) not in matched_det_ids:
-                trk = KalmanBoxTracker(dets[dg])
+            orig_idx = int(remain_orig_idx[int(dg)])
+            if orig_idx not in matched_det_ids:
+                trk = KalmanBoxTracker(dets[int(dg)])
                 self.tracked_tracks.append(trk)
-                det_to_track[int(dg)] = trk.track_id
+                det_to_track[orig_idx] = trk.track_id
                 tracked_map[trk.track_id] = trk.get_cx()
 
         return tracked_map, det_to_track, lost_map
@@ -749,61 +765,59 @@ def draw_hero_count(img, line_x, h, count, pulse_remaining=0):
     text = str(count)
     font = cv2.FONT_HERSHEY_SIMPLEX
     boost = 0.35 * (pulse_remaining / max(COUNT_PULSE_FRAMES, 1))
-    font_scale, thickness = 1.6 + boost, 3
+    font_scale, thickness = 1.4 + boost, 3
     (tw, th), _ = cv2.getTextSize(text, font, font_scale, thickness)
     pad = 14
-    tx, ty = line_x - tw // 2, h // 2 + th // 2
+    tx, ty = line_x - tw // 2, h // 3 + th // 2
     overlay_rect(
-        img, tx - pad, ty - th - pad, tx + tw + pad, ty + pad // 2, C_PANEL, alpha=0.78
+        img, tx - pad, ty - th - pad, tx + tw + pad, ty + pad, C_PANEL, alpha=0.78
     )
     cv2.rectangle(
-        img, (tx - pad, ty - th - pad), (tx + tw + pad, ty + pad // 2), C_LINE_CORE, 2
+        img, (tx - pad, ty - th - pad), (tx + tw + pad, ty + pad), 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
-):
-    bar_h = 52
+def draw_hud(img, w, batch_num, batch_count, total_ayam, elapsed_sec, rate):
+    bar_h = 40
     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
+        img, "BATCH", (14, 14), cv2.FONT_HERSHEY_SIMPLEX, 0.32, C_MUTED, 1, cv2.LINE_AA
     )
-    batch_label = str(batch_num) if batch_num else "\u2014"
+    batch_label = str(batch_num) if batch_num else "--"
     cv2.putText(
         img,
         batch_label,
-        (16, 44),
+        (14, 32),
         cv2.FONT_HERSHEY_SIMPLEX,
-        0.9,
+        0.55,
         C_ACCENT,
-        2,
+        1,
         cv2.LINE_AA,
     )
     cv2.putText(
-        img, "COUNT", (100, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+        img, "COUNT", (90, 14), cv2.FONT_HERSHEY_SIMPLEX, 0.32, C_MUTED, 1, cv2.LINE_AA
     )
     cv2.putText(
         img,
         str(batch_count),
-        (100, 44),
+        (90, 32),
         cv2.FONT_HERSHEY_SIMPLEX,
-        0.9,
+        0.55,
         C_GREEN,
-        2,
+        1,
         cv2.LINE_AA,
     )
     cv2.putText(
-        img, "TOTAL", (190, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+        img, "TOTAL", (170, 14), cv2.FONT_HERSHEY_SIMPLEX, 0.32, C_MUTED, 1, cv2.LINE_AA
     )
     cv2.putText(
         img,
         str(total_ayam),
-        (190, 44),
+        (170, 32),
         cv2.FONT_HERSHEY_SIMPLEX,
-        0.7,
+        0.45,
         C_TEXT,
         1,
         cv2.LINE_AA,
@@ -811,9 +825,9 @@ def draw_hud(
     cv2.putText(
         img,
         "UPTIME",
-        (280, 20),
+        (250, 14),
         cv2.FONT_HERSHEY_SIMPLEX,
-        0.45,
+        0.32,
         C_MUTED,
         1,
         cv2.LINE_AA,
@@ -821,45 +835,34 @@ def draw_hud(
     cv2.putText(
         img,
         f"{elapsed_sec / 3600:.1f}h",
-        (280, 44),
+        (250, 32),
         cv2.FONT_HERSHEY_SIMPLEX,
-        0.7,
+        0.45,
         C_TEXT,
         1,
         cv2.LINE_AA,
     )
     cv2.putText(
-        img, "RATE", (380, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv2.LINE_AA
+        img, "RATE", (340, 14), cv2.FONT_HERSHEY_SIMPLEX, 0.32, C_MUTED, 1, cv2.LINE_AA
     )
     cv2.putText(
         img,
         f"{rate:.1f}/min",
-        (380, 44),
+        (340, 32),
         cv2.FONT_HERSHEY_SIMPLEX,
-        0.7,
+        0.45,
         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):
+def draw_footer(img, w, h, frame_idx, live_tag, inf_ms=0.0, model_name=""):
     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}",
+        f"{live_tag} | {model_name} | Frame {frame_idx} | Inf {inf_ms:.1f}ms",
         (12, h - 9),
         cv2.FONT_HERSHEY_SIMPLEX,
         0.45,
@@ -982,26 +985,22 @@ def run():
         score_sigmoid=SCORE_SIGMOID,
     )
 
-    CLASS_IDS = {
-        os.getenv("CLASS_AYAM", "ayam"): 0,
-        os.getenv("CLASS_TALENAN", "talenan"): 1,
-    }
-    ayam_cls = CLASS_IDS[CLASS_AYAM]
-    talenan_cls = CLASS_IDS[CLASS_TALENAN]
+    ayam_cls = int(os.getenv("AYAM_CLASS_ID", "0"))
+    talenan_cls = int(os.getenv("TALENAN_CLASS_ID", "1"))
 
     ayam_tracker = ByteTracker(
-        track_high_thresh=TRACK_HIGH_THRESH,
-        track_low_thresh=TRACK_LOW_THRESH,
-        match_thresh=TRACK_MATCH_THRESH,
-        track_buffer=TRACK_BUFFER,
-        min_hits=TRACK_MIN_HITS,
+        track_high_thresh=TRACK_HIGH_THRESH_0,
+        track_low_thresh=TRACK_LOW_THRESH_0,
+        match_thresh=TRACK_MATCH_THRESH_0,
+        track_buffer=TRACK_BUFFER_0,
+        min_hits=TRACK_MIN_HITS_0,
     )
     talenan_tracker = ByteTracker(
-        track_high_thresh=TRACK_HIGH_THRESH,
-        track_low_thresh=TRACK_LOW_THRESH,
-        match_thresh=TRACK_MATCH_THRESH,
-        track_buffer=TRACK_BUFFER,
-        min_hits=TRACK_MIN_HITS,
+        track_high_thresh=TRACK_HIGH_THRESH_1,
+        track_low_thresh=TRACK_LOW_THRESH_1,
+        match_thresh=TRACK_MATCH_THRESH_1,
+        track_buffer=TRACK_BUFFER_1,
+        min_hits=TRACK_MIN_HITS_1,
     )
 
     ayam_line_crossed = set()
@@ -1014,7 +1013,9 @@ def run():
 
     session_start = time.time()
     frame_idx = 0
+    inf_ms = 0.0
     video_writer = None
+    crossing_times = deque()
 
     cap, w, h, fps = connect_stream(SOURCE)
     if cap is None:
@@ -1028,8 +1029,12 @@ def run():
     )
     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}"
+        f"ByteTrack Index 0: high_thresh={TRACK_HIGH_THRESH_0} low_thresh={TRACK_LOW_THRESH_0} "
+        f"match_thresh={TRACK_MATCH_THRESH_0} buffer={TRACK_BUFFER_0}"
+    )
+    print(
+        f"ByteTrack Index 1: high_thresh={TRACK_HIGH_THRESH_1} low_thresh={TRACK_LOW_THRESH_1} "
+        f"match_thresh={TRACK_MATCH_THRESH_1} buffer={TRACK_BUFFER_1}"
     )
     print(f"DB: {DB_PATH}")
     print(f"State: {STATE_FILE}")
@@ -1061,7 +1066,9 @@ def run():
         mono = time.monotonic()
         ayam_crossed_frame = batch_closed_frame = batch_started_frame = False
 
+        inf_start = time.time()
         detections = model(frame)
+        inf_ms = inf_ms * 0.9 + (time.time() - inf_start) * 1000 * 0.1
 
         if detections:
             ayam_boxes_xyxy = []
@@ -1104,6 +1111,56 @@ def run():
                 talenan_tracker.update(talenan_boxes_xyxy, talenan_scores)
             )
 
+            if os.getenv("DEBUG_TRACKING", "").lower() == "true":
+                if len(ayam_boxes_xyxy) > 0 or len(talenan_boxes_xyxy) > 0:
+                    ayam_scores_str = (
+                        f"  ayam scores: {ayam_scores.round(3).tolist()}"
+                        if len(ayam_scores) > 0
+                        else ""
+                    )
+                    talenan_scores_str = (
+                        f"  talenan scores: {talenan_scores.round(3).tolist()}"
+                        if len(talenan_scores) > 0
+                        else ""
+                    )
+                    ayam_tracks_str = (
+                        f"  ayam det→track: {dict(ayam_det_to_track)}"
+                        if ayam_det_to_track
+                        else ""
+                    )
+                    talenan_tracks_str = (
+                        f"  talenan det→track: {dict(talenan_det_to_track)}"
+                        if talenan_det_to_track
+                        else ""
+                    )
+                    crossing_str = (
+                        f"  ayam_line_crossed: {sorted(ayam_line_crossed)}"
+                        if ayam_line_crossed
+                        else ""
+                    )
+                    # Show cx values for one tracked object to check movement
+                    cx_sample = ""
+                    if len(ayam_cx_list) > 0 and ayam_det_to_track:
+                        sample_tid = list(ayam_det_to_track.values())[0]
+                        sample_cx = ayam_cx_list[
+                            list(ayam_det_to_track.keys())[0]
+                        ]
+                        prev = (
+                            ayam_tracked.get(sample_tid, (None,))[0]
+                            if ayam_tracked.get(sample_tid)
+                            else None
+                        )
+                        cx_sample = (
+                            f"  sample tid={sample_tid} prev_cx={prev} cx={sample_cx:.1f}"
+                        )
+                    print(
+                        f"[DEBUG F{frame_idx}] ayam_dets={len(ayam_boxes_xyxy)} "
+                        f"talenan_dets={len(talenan_boxes_xyxy)} "
+                        f"line_x={line_x}{ayam_scores_str}{talenan_scores_str}"
+                        f"{ayam_tracks_str}{talenan_tracks_str}{crossing_str}"
+                        f"{cx_sample}"
+                    )
+
             # Process talenan crossings
             for di in range(len(talenan_boxes_xyxy)):
                 tid = talenan_det_to_track.get(di)
@@ -1145,6 +1202,11 @@ def run():
                         crossed_line(prev_cx, cx, line_x)
                         and tid not in ayam_line_crossed
                     ):
+                        if os.getenv("DEBUG_TRACKING", "").lower() == "true":
+                            print(
+                                f"[DEBUG F{frame_idx}] CROSS DETECTED: tid={tid} "
+                                f"prev_cx={prev_cx:.1f} → cx={cx:.1f} line_x={line_x}"
+                            )
                         ayam_line_crossed.add(tid)
                         _, started_new = store.record_ayam_crossing(tid)
                         if cross_logger:
@@ -1159,6 +1221,7 @@ def run():
                         ayam_crossed_frame = True
                         if started_new:
                             batch_started_frame = True
+                        crossing_times.append(mono)
                         ayam_cross_flash[tid] = CROSS_FLASH_FRAMES
                         popups.append(
                             {
@@ -1216,7 +1279,9 @@ def run():
         batch_num = store.current_batch_number or 0
         batch_count = store.current_batch_count
         display_total = store.display_total()
-        rate = (display_total / elapsed * 60) if elapsed > 0 else 0.0
+        while crossing_times and mono - crossing_times[0] > RATE_WINDOW_SEC:
+            crossing_times.popleft()
+        rate = (len(crossing_times) / RATE_WINDOW_SEC * 60) if crossing_times else 0.0
 
         draw_elegant_counting_line(frame, line_x, h, line_pulse)
         draw_hero_count(frame, line_x, h, batch_count, count_pulse)
@@ -1228,12 +1293,16 @@ def run():
             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"
+            frame,
+            w,
+            h,
+            frame_idx,
+            "LIVE" if IS_LIVE else "FILE",
+            inf_ms,
+            Path(MODEL_PATH).name,
         )
         popups = draw_popups(frame, popups, frame_idx)
 

src/config.cpp

@@ -73,17 +73,35 @@ void AppConfig::load_from_env(const char* env_path) {
     if (!nc_s.empty()) num_classes = std::stoi(nc_s);
     auto ss_s = get_env("SCORE_SIGMOID");
     score_sigmoid = (ss_s == "true");
+    auto ac_s = get_env("AYAM_CLASS_ID");
+    if (!ac_s.empty()) ayam_class_id = std::stoi(ac_s);
+    auto tc_s = get_env("TALENAN_CLASS_ID");
+    if (!tc_s.empty()) talenan_class_id = std::stoi(tc_s);
 
-    auto th_s = get_env("TRACK_HIGH_THRESH");
-    if (!th_s.empty()) track_high_thresh = std::stof(th_s);
-    auto tl_s = get_env("TRACK_LOW_THRESH");
-    if (!tl_s.empty()) track_low_thresh = std::stof(tl_s);
-    auto tm_s = get_env("TRACK_MATCH_THRESH");
-    if (!tm_s.empty()) track_match_thresh = std::stof(tm_s);
-    auto tb_s = get_env("TRACK_BUFFER");
-    if (!tb_s.empty()) track_buffer = std::stoi(tb_s);
-    auto tmh_s = get_env("TRACK_MIN_HITS");
-    if (!tmh_s.empty()) track_min_hits = std::stoi(tmh_s);
+    auto th0_s = get_env("TRACK_HIGH_THRESH_0");
+    if (!th0_s.empty()) track_high_thresh_0 = std::stof(th0_s);
+    auto tl0_s = get_env("TRACK_LOW_THRESH_0");
+    if (!tl0_s.empty()) track_low_thresh_0 = std::stof(tl0_s);
+    auto tm0_s = get_env("TRACK_MATCH_THRESH_0");
+    if (!tm0_s.empty()) track_match_thresh_0 = std::stof(tm0_s);
+    auto tb0_s = get_env("TRACK_BUFFER_0");
+    if (!tb0_s.empty()) track_buffer_0 = std::stoi(tb0_s);
+    auto tmh0_s = get_env("TRACK_MIN_HITS_0");
+    if (!tmh0_s.empty()) track_min_hits_0 = std::stoi(tmh0_s);
+
+    auto th1_s = get_env("TRACK_HIGH_THRESH_1");
+    if (!th1_s.empty()) track_high_thresh_1 = std::stof(th1_s);
+    auto tl1_s = get_env("TRACK_LOW_THRESH_1");
+    if (!tl1_s.empty()) track_low_thresh_1 = std::stof(tl1_s);
+    auto tm1_s = get_env("TRACK_MATCH_THRESH_1");
+    if (!tm1_s.empty()) track_match_thresh_1 = std::stof(tm1_s);
+    auto tb1_s = get_env("TRACK_BUFFER_1");
+    if (!tb1_s.empty()) track_buffer_1 = std::stoi(tb1_s);
+    auto tmh1_s = get_env("TRACK_MIN_HITS_1");
+    if (!tmh1_s.empty()) track_min_hits_1 = std::stoi(tmh1_s);
+
+    auto rw_s = get_env("RATE_WINDOW_SEC");
+    if (!rw_s.empty()) rate_window_sec = std::stoi(rw_s);
 
     daily_cutoff_time = get_env("DAILY_CUTOFF_TIME", daily_cutoff_time);
     auto bto_s = get_env("BATCH_TIMEOUT_SECONDS");

src/config.hpp

@@ -24,12 +24,22 @@ struct AppConfig {
     int core_mask = 1;
     int num_classes = 2;
     bool score_sigmoid = false;
+    int ayam_class_id = 0;
+    int talenan_class_id = 1;
 
-    float track_high_thresh = 0.5f;
-    float track_low_thresh = 0.1f;
-    float track_match_thresh = 0.8f;
-    int track_buffer = 30;
-    int track_min_hits = 3;
+    float track_high_thresh_0 = 0.5f;
+    float track_low_thresh_0 = 0.1f;
+    float track_match_thresh_0 = 0.8f;
+    int track_buffer_0 = 30;
+    int track_min_hits_0 = 3;
+
+    float track_high_thresh_1 = 0.5f;
+    float track_low_thresh_1 = 0.1f;
+    float track_match_thresh_1 = 0.6f;
+    int track_buffer_1 = 30;
+    int track_min_hits_1 = 3;
+
+    int rate_window_sec = 60;
 
     std::string daily_cutoff_time = "20:00";
     float batch_timeout_seconds = 300.0f;

src/drawing.cpp

@@ -9,8 +9,8 @@ const std::vector<std::pair<int, int>> SKELETON = {
 };
 
 const std::vector<cv::Scalar> SK_COLORS = {
-    {255, 255, 0}, {255, 255, 0}, {255, 0, 255}, {255, 0, 255},
-    {0, 255, 0}, {255, 255, 0}, {255, 0, 0}, {0, 200, 200}
+    {0, 255, 255}, {0, 255, 255}, {255, 0, 255}, {255, 0, 255},
+    {0, 255, 0}, {255, 255, 0}, {0, 0, 255}, {200, 200, 0}
 };
 
 int resolve_line_x(int frame_width, int line_x_opt, float line_x_frac) {
@@ -68,54 +68,53 @@ void draw_elegant_counting_line(cv::Mat& img, int line_x, int h, int pulse_remai
 void draw_hero_count(cv::Mat& img, int line_x, int h, int count, int pulse_remaining) {
     std::string text = std::to_string(count);
     float boost = 0.35f * (pulse_remaining / std::max(15.0f, 1.0f));
-    double font_scale = 1.6 + boost;
+    double font_scale = 1.4 + boost;
     int thickness = static_cast<int>(3 + boost);
     int baseline = 0;
     cv::Size ts = cv::getTextSize(text, cv::FONT_HERSHEY_SIMPLEX, font_scale, thickness, &baseline);
     int pad = 14;
     int tx = line_x - ts.width / 2;
-    int ty = h / 2 + ts.height / 2;
-    overlay_rect(img, tx - pad, ty - ts.height - pad, tx + ts.width + pad, ty + pad / 2, C_PANEL, 0.78f);
+    int ty = h / 3 + ts.height / 2;
+    overlay_rect(img, tx - pad, ty - ts.height - pad, tx + ts.width + pad, ty + pad, C_PANEL, 0.78f);
     cv::rectangle(img, cv::Rect(tx - pad, ty - ts.height - pad,
-                                ts.width + pad * 2, ts.height + pad + pad / 2),
+                                ts.width + pad * 2, ts.height + pad * 2),
                   C_LINE_CORE, 2);
     cv::putText(img, text, cv::Point(tx, ty), cv::FONT_HERSHEY_SIMPLEX, font_scale, C_GREEN, thickness, cv::LINE_AA);
 }
 
 void draw_hud(cv::Mat& img, int w, int batch_num, int batch_count, int total_ayam,
-              double elapsed_sec, double rate, const std::string& camera_id, const std::string& clock) {
-    int bar_h = 52;
+              double elapsed_sec, double rate) {
+    int bar_h = 40;
     overlay_rect(img, 0, 0, w, bar_h, C_PANEL, 0.72f);
     cv::line(img, cv::Point(0, bar_h), cv::Point(w, bar_h), C_BORDER, 1);
 
-    cv::putText(img, "BATCH", cv::Point(16, 20), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv::LINE_AA);
-    std::string batch_label = batch_num ? std::to_string(batch_num) : "\xe2\x80\x94";
-    cv::putText(img, batch_label, cv::Point(16, 44), cv::FONT_HERSHEY_SIMPLEX, 0.9, C_ACCENT, 2, cv::LINE_AA);
+    cv::putText(img, "BATCH", cv::Point(14, 14), cv::FONT_HERSHEY_SIMPLEX, 0.32, C_MUTED, 1, cv::LINE_AA);
+    std::string batch_label = batch_num ? std::to_string(batch_num) : "--";
+    cv::putText(img, batch_label, cv::Point(14, 32), cv::FONT_HERSHEY_SIMPLEX, 0.55, C_ACCENT, 1, cv::LINE_AA);
 
-    cv::putText(img, "COUNT", cv::Point(100, 20), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv::LINE_AA);
-    cv::putText(img, std::to_string(batch_count), cv::Point(100, 44), cv::FONT_HERSHEY_SIMPLEX, 0.9, C_GREEN, 2, cv::LINE_AA);
+    cv::putText(img, "COUNT", cv::Point(90, 14), cv::FONT_HERSHEY_SIMPLEX, 0.32, C_MUTED, 1, cv::LINE_AA);
+    cv::putText(img, std::to_string(batch_count), cv::Point(90, 32), cv::FONT_HERSHEY_SIMPLEX, 0.55, C_GREEN, 1, cv::LINE_AA);
 
-    cv::putText(img, "TOTAL", cv::Point(190, 20), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv::LINE_AA);
-    cv::putText(img, std::to_string(total_ayam), cv::Point(190, 44), cv::FONT_HERSHEY_SIMPLEX, 0.7, C_TEXT, 1, cv::LINE_AA);
+    cv::putText(img, "TOTAL", cv::Point(170, 14), cv::FONT_HERSHEY_SIMPLEX, 0.32, C_MUTED, 1, cv::LINE_AA);
+    cv::putText(img, std::to_string(total_ayam), cv::Point(170, 32), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_TEXT, 1, cv::LINE_AA);
 
-    cv::putText(img, "UPTIME", cv::Point(280, 20), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv::LINE_AA);
+    cv::putText(img, "UPTIME", cv::Point(250, 14), cv::FONT_HERSHEY_SIMPLEX, 0.32, C_MUTED, 1, cv::LINE_AA);
     char buf[32];
     snprintf(buf, sizeof(buf), "%.1fh", elapsed_sec / 3600.0);
-    cv::putText(img, buf, cv::Point(280, 44), cv::FONT_HERSHEY_SIMPLEX, 0.7, C_TEXT, 1, cv::LINE_AA);
+    cv::putText(img, buf, cv::Point(250, 32), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_TEXT, 1, cv::LINE_AA);
 
-    cv::putText(img, "RATE", cv::Point(380, 20), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv::LINE_AA);
+    cv::putText(img, "RATE", cv::Point(340, 14), cv::FONT_HERSHEY_SIMPLEX, 0.32, C_MUTED, 1, cv::LINE_AA);
     snprintf(buf, sizeof(buf), "%.1f/min", rate);
-    cv::putText(img, buf, cv::Point(380, 44), cv::FONT_HERSHEY_SIMPLEX, 0.7, C_ACCENT, 1, cv::LINE_AA);
-
-    std::string cam_label = "CAM " + camera_id;
-    cv::putText(img, cam_label, cv::Point(w - 180, 20), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv::LINE_AA);
+    cv::putText(img, buf, cv::Point(340, 32), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_ACCENT, 1, cv::LINE_AA);
 }
 
-void draw_footer(cv::Mat& img, int w, int h, int frame_idx, const std::string& live_tag) {
+void draw_footer(cv::Mat& img, int w, int h, int frame_idx, const std::string& live_tag,
+                 float inf_ms, const std::string& model_name) {
     int bar_h = 28;
     overlay_rect(img, 0, h - bar_h, w, h, C_PANEL, 0.55f);
-    char buf[64];
-    snprintf(buf, sizeof(buf), "%s | Frame %d", live_tag.c_str(), frame_idx);
+    char buf[128];
+    snprintf(buf, sizeof(buf), "%s | %s | Frame %d | Inf %.1fms",
+             live_tag.c_str(), model_name.c_str(), frame_idx, inf_ms);
     cv::putText(img, buf, cv::Point(12, h - 9), cv::FONT_HERSHEY_SIMPLEX, 0.45, C_MUTED, 1, cv::LINE_AA);
 }
 

src/drawing.hpp

@@ -5,16 +5,16 @@
 #include <tuple>
 #include <cstdint>
 
-inline const cv::Scalar C_PANEL(18, 24, 28);
-inline const cv::Scalar C_BORDER(75, 85, 90);
-inline const cv::Scalar C_ACCENT(60, 200, 255);
-inline const cv::Scalar C_GREEN(100, 220, 80);
+inline const cv::Scalar C_PANEL(28, 24, 18);
+inline const cv::Scalar C_BORDER(90, 85, 75);
+inline const cv::Scalar C_ACCENT(255, 200, 60);
+inline const cv::Scalar C_GREEN(80, 220, 100);
 inline const cv::Scalar C_TEXT(235, 235, 235);
 inline const cv::Scalar C_MUTED(150, 150, 150);
-inline const cv::Scalar C_AYAM_BOX(255, 165, 0);
-inline const cv::Scalar C_TALENAN_BOX(60, 120, 220);
-inline const cv::Scalar C_LINE_CORE(255, 220, 180);
-inline const cv::Scalar C_LINE_GLOW(220, 160, 100);
+inline const cv::Scalar C_AYAM_BOX(255, 150, 60);
+inline const cv::Scalar C_TALENAN_BOX(60, 60, 255);
+inline const cv::Scalar C_LINE_CORE(180, 220, 255);
+inline const cv::Scalar C_LINE_GLOW(100, 160, 220);
 
 extern const std::vector<std::pair<int, int>> SKELETON;
 extern const std::vector<cv::Scalar> SK_COLORS;
@@ -30,8 +30,9 @@ void draw_pill(cv::Mat& img, const std::string& text, int x, int y,
 void draw_elegant_counting_line(cv::Mat& img, int line_x, int h, int pulse_remaining = 0);
 void draw_hero_count(cv::Mat& img, int line_x, int h, int count, int pulse_remaining = 0);
 void draw_hud(cv::Mat& img, int w, int batch_num, int batch_count, int total_ayam,
-              double elapsed_sec, double rate, const std::string& camera_id, const std::string& clock);
-void draw_footer(cv::Mat& img, int w, int h, int frame_idx, const std::string& live_tag);
+              double elapsed_sec, double rate);
+void draw_footer(cv::Mat& img, int w, int h, int frame_idx, const std::string& live_tag,
+                 float inf_ms = 0.0f, const std::string& model_name = "");
 void draw_skeleton_bold(cv::Mat& img, const std::vector<std::vector<cv::Point2f>>& kpts);
 
 struct Popup {

src/main.cpp

@@ -50,6 +50,35 @@ static void warmup_stream(cv::VideoCapture& cap, int n) {
     std::cout << "Stream ready!" << std::endl;
 }
 
+static bool connect_stream(cv::VideoCapture& cap, int& w, int& h, double& fps) {
+    bool is_live = g_config.source.substr(0, 7) == "rtsp://" ||
+                   g_config.source.substr(0, 7) == "http://";
+    int attempts = 0;
+    while (!shutdown_requested) {
+        cap = open_capture(g_config.source);
+        if (cap.isOpened()) break;
+        attempts++;
+        if (g_config.max_reconnect_attempts > 0 && attempts >= g_config.max_reconnect_attempts) {
+            std::cerr << "Cannot open source after " << attempts
+                      << " attempts: " << g_config.source << std::endl;
+            return false;
+        }
+        std::cout << "Cannot open source, retry in " << g_config.reconnect_delay_sec
+                  << "s..." << std::endl;
+        std::this_thread::sleep_for(std::chrono::seconds(g_config.reconnect_delay_sec));
+    }
+    if (shutdown_requested) return false;
+
+    if (is_live && g_config.warmup_frames > 0)
+        warmup_stream(cap, g_config.warmup_frames);
+
+    w = static_cast<int>(cap.get(cv::CAP_PROP_FRAME_WIDTH));
+    h = static_cast<int>(cap.get(cv::CAP_PROP_FRAME_HEIGHT));
+    fps = cap.get(cv::CAP_PROP_FPS);
+    if (fps <= 1) fps = g_config.output_fps;
+    return true;
+}
+
 struct TrackedInfo {
     float cx;
     std::chrono::steady_clock::time_point ts;
@@ -75,11 +104,23 @@ int main(int argc, char* argv[]) {
     std::cout << "Starting ByteTrack Counter (C++)" << std::endl;
     std::cout << "Camera: " << g_config.camera_name << std::endl;
     std::cout << "Source: " << g_config.source << std::endl;
-    std::cout << "Model: " << g_config.model_path << std::endl;
+    std::cout << "Model: " << g_config.model_path << " | imgsz=" << g_config.imgsz
+              << " | core_mask=" << g_config.core_mask << std::endl;
     std::cout << "DB: " << g_config.db_path << std::endl;
+    std::cout << "State: " << g_config.state_file << std::endl;
+    std::cout << "ByteTrack Index 0: high_thresh=" << g_config.track_high_thresh_0
+              << " low_thresh=" << g_config.track_low_thresh_0
+              << " match_thresh=" << g_config.track_match_thresh_0
+              << " buffer=" << g_config.track_buffer_0
+              << " min_hits=" << g_config.track_min_hits_0 << std::endl;
+    std::cout << "ByteTrack Index 1: high_thresh=" << g_config.track_high_thresh_1
+              << " low_thresh=" << g_config.track_low_thresh_1
+              << " match_thresh=" << g_config.track_match_thresh_1
+              << " buffer=" << g_config.track_buffer_1
+              << " min_hits=" << g_config.track_min_hits_1 << std::endl;
 
-    int class_ayam = 0;
-    int class_talenan = 1;
+    int class_ayam = g_config.ayam_class_id;
+    int class_talenan = g_config.talenan_class_id;
 
     auto logger = [](const std::string& msg) {
         std::cout << "[" << now_str() << "] " << msg << std::endl;
@@ -105,12 +146,12 @@ int main(int argc, char* argv[]) {
                    g_config.imgsz, g_config.conf, 0.45f,
                    g_config.num_classes, 0, g_config.score_sigmoid);
 
-    ByteTracker ayam_tracker(g_config.track_high_thresh, g_config.track_low_thresh,
-                              g_config.track_match_thresh, g_config.track_buffer,
-                              g_config.track_min_hits);
-    ByteTracker talenan_tracker(g_config.track_high_thresh, g_config.track_low_thresh,
-                                 g_config.track_match_thresh, g_config.track_buffer,
-                                 g_config.track_min_hits);
+    ByteTracker ayam_tracker(g_config.track_high_thresh_0, g_config.track_low_thresh_0,
+                              g_config.track_match_thresh_0, g_config.track_buffer_0,
+                              g_config.track_min_hits_0);
+    ByteTracker talenan_tracker(g_config.track_high_thresh_1, g_config.track_low_thresh_1,
+                                 g_config.track_match_thresh_1, g_config.track_buffer_1,
+                                 g_config.track_min_hits_1);
 
     std::unordered_set<int> ayam_line_crossed;
     std::unordered_set<int> talenan_line_crossed;
@@ -119,27 +160,27 @@ int main(int argc, char* argv[]) {
     std::unordered_map<int, int> talenan_cross_flash;
     int line_pulse = 0, count_pulse = 0, batch_pulse = 0;
     std::vector<Popup> popups;
+    std::deque<std::chrono::steady_clock::time_point> crossing_times;
 
     auto session_start = std::chrono::steady_clock::now();
     int frame_idx = 0;
+    float inf_ema = 0.0f;
 
-    cv::VideoCapture cap = open_capture(g_config.source);
+    std::string model_name = g_config.model_path;
+    auto slash = model_name.find_last_of("/\\");
+    if (slash != std::string::npos) model_name = model_name.substr(slash + 1);
+
+    cv::VideoCapture cap;
+    int w, h;
+    double fps_prop;
+
+    if (!connect_stream(cap, w, h, fps_prop)) {
+        store.shutdown();
+        return shutdown_requested ? 0 : 1;
+    }
     bool is_live = g_config.source.substr(0, 7) == "rtsp://" ||
                    g_config.source.substr(0, 7) == "http://";
 
-    if (!cap.isOpened()) {
-        std::cerr << "Cannot open source: " << g_config.source << std::endl;
-        store.shutdown();
-        return 1;
-    }
-    if (is_live && g_config.warmup_frames > 0)
-        warmup_stream(cap, g_config.warmup_frames);
-
-    int w = static_cast<int>(cap.get(cv::CAP_PROP_FRAME_WIDTH));
-    int h = static_cast<int>(cap.get(cv::CAP_PROP_FRAME_HEIGHT));
-    double fps_prop = cap.get(cv::CAP_PROP_FPS);
-    if (fps_prop <= 1) fps_prop = g_config.output_fps;
-
     int line_x = resolve_line_x(w, g_config.line_x, g_config.line_x_frac);
 
     std::cout << "RKNN+ByteTrack counter | " << w << "x" << h << " @ "
@@ -161,21 +202,22 @@ int main(int argc, char* argv[]) {
                       << "), reconnecting..." << std::endl;
             cap.release();
             std::this_thread::sleep_for(std::chrono::seconds(g_config.reconnect_delay_sec));
-            cap = open_capture(g_config.source);
-            if (!cap.isOpened()) break;
-            w = static_cast<int>(cap.get(cv::CAP_PROP_FRAME_WIDTH));
-            h = static_cast<int>(cap.get(cv::CAP_PROP_FRAME_HEIGHT));
+            if (!connect_stream(cap, w, h, fps_prop)) break;
             line_x = resolve_line_x(w, g_config.line_x, g_config.line_x_frac);
             continue;
         }
 
-        auto elapsed_sec = std::chrono::duration_cast<std::chrono::seconds>(
+        auto elapsed_sec = std::chrono::duration<double>(
             std::chrono::steady_clock::now() - session_start).count();
         auto mono = std::chrono::steady_clock::now();
 
         bool ayam_crossed_frame = false, batch_closed_frame = false, batch_started_frame = false;
 
+        auto inf_start = std::chrono::steady_clock::now();
         std::vector<Detection> detections = model(frame);
+        float inf_ms = std::chrono::duration<float, std::milli>(
+            std::chrono::steady_clock::now() - inf_start).count();
+        inf_ema = inf_ema * 0.9f + inf_ms * 0.1f;
 
         if (!detections.empty()) {
             std::vector<Eigen::Vector4f> ayam_boxes, talenan_boxes;
@@ -317,6 +359,7 @@ int main(int argc, char* argv[]) {
                         }
                         ayam_crossed_frame = true;
                         if (started_new) batch_started_frame = true;
+                        crossing_times.push_back(mono);
                         ayam_cross_flash[tid] = g_config.cross_flash_frames;
                         popups.push_back({
                             static_cast<int>(cx) - 12,
@@ -379,15 +422,19 @@ int main(int argc, char* argv[]) {
         int batch_num = store.current_batch_number();
         int batch_count = store.current_batch_count();
         int display_total = store.display_total();
-        double elapsed = static_cast<double>(elapsed_sec);
-        double rate = elapsed > 0 ? (display_total / elapsed * 60.0) : 0.0;
+
+        while (!crossing_times.empty() &&
+               std::chrono::duration<double>(mono - crossing_times.front()).count() > g_config.rate_window_sec)
+            crossing_times.pop_front();
+        double rate = crossing_times.empty() ? 0.0 :
+            (crossing_times.size() / static_cast<double>(g_config.rate_window_sec) * 60.0);
 
         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, g_config.camera_name, now_str());
+                 elapsed_sec, rate);
         draw_batch_banner(frame, w, batch_num, batch_pulse);
-        draw_footer(frame, w, h, frame_idx, is_live ? "LIVE-RKNN-BT" : "FILE-RKNN-BT");
+        draw_footer(frame, w, h, frame_idx, is_live ? "LIVE" : "FILE", inf_ema, model_name);
         popups = draw_popups(frame, popups, frame_idx);
 
         // Flash decay
@@ -418,9 +465,10 @@ int main(int argc, char* argv[]) {
         frame_idx++;
         if (frame_idx % g_config.flush_every_n_frames == 0) {
             std::cout << "[" << now_str() << "] Frame " << frame_idx
-                      << " | Batch " << batch_num << ": " << batch_count
+                      << " | Batch " << (batch_num ? std::to_string(batch_num) : "-")
+                      << ": " << (batch_num ? std::to_string(batch_count) : "-")
                       << " | Total: " << display_total
-                      << " | Uptime " << (elapsed / 3600.0) << "h" << std::endl;
+                       << " | Uptime " << (elapsed_sec / 3600.0) << "h" << std::endl;
         }
 
         prune_stale_tracks(ayam_tracked, g_config.tracked_prune_sec);