config.env.example

@@ -1,30 +1,39 @@
 # =============================================================================
-# DEPRECATED — use env.example instead.
-#
-#   cp env.example .env && nano .env
-#
-# This file is kept for backward compatibility only. All new deployments should
-# use env.example as the single canonical template. See DEPLOY.md.
+# 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 ---
-OUTPUT_DIR=/opt/zenai-kpc-counter
-DB_PATH=/opt/zenai-kpc-counter/counter.db
-STATE_FILE=/opt/zenai-kpc-counter/current_counter.json
+# Root output directory (logs, DB, video, CSV)
+OUTPUT_DIR=/opt/bytetrack-counter
+# SQLite database path for daily counter records & crossing logs
+DB_PATH=/opt/bytetrack-counter/bytetrack_counter.db
+# JSON file persisting the current active counting day state
+STATE_FILE=/tmp/bytetrack_current_counter.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 ---
-MODEL_PATH=/opt/models/your_model.rknn
+# 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
-CORE_MASK=1
+# 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 ---
-NUM_CLASSES=4
+# Number of object classes the model outputs
+NUM_CLASSES=2
+# Apply sigmoid to raw class scores (true/false); set true if model head uses BCE logits
 SCORE_SIGMOID=false
 
 # --- Detection ---
@@ -37,55 +46,117 @@ CONF=0.3
 NMS_IOU=0.45
 
 # --- ByteTrack tracking ---
+# Detections with score >= this get priority matching in the first association stage
 TRACK_HIGH_THRESH=0.5
-TRACK_LOW_THRESH=0.3
-TRACK_MATCH_THRESH=0.7
-TRACK_BUFFER=60
+# Detections with score between this and TRACK_HIGH_THRESH are matched in the second stage
+TRACK_LOW_THRESH=0.1
+# IoU threshold for the first-stage association (0–1). Higher = stricter overlap required
+TRACK_MATCH_THRESH=0.8
+# Frames a track survives without a match before being permanently removed
+TRACK_BUFFER=30
+# Minimum consecutive (or total) hits needed before a track is considered confirmed
 TRACK_MIN_HITS=3
 
 # --- ID-switch counting guards ---
+# When a track's ID changes right at the counting line, one physical object can be
+# counted twice (two IDs cross) or missed (neither ID sees the full transition).
+# These two guards correct for that.
+#
+# Dedup guard (prevents double counting): after a crossing, a second crossing in
+# the SAME direction within DEDUP_FRAMES frames and DEDUP_PX horizontal pixels is
+# ignored (treated as the same object under a new ID).
 DEDUP_FRAMES=15
 DEDUP_PX=60
+# To DISABLE the dedup guard, set DEDUP_PX=-1 (distance check can never match).
+#
+# Inheritance guard (prevents missed counting): when a brand-new track appears, it
+# inherits the last position of a recently-seen nearby track (within INHERIT_SEC
+# seconds and INHERIT_PX horizontal pixels) so the crossing is still detected
+# across the ID switch.
 INHERIT_SEC=1.0
 INHERIT_PX=60
+# To DISABLE the inheritance guard, set INHERIT_PX=-1 (distance check can never match).
 
 # --- 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
-OBJECT_LABEL=karung
-CLASS_OBJECT=karung
+# Label used for batch grouping in the database
+OBJECT_LABEL=object
+# Class name for the counted object (must match model class order)
+CLASS_OBJECT=object
+# Model class ID for the object being counted (default 0)
 OBJECT_CLASS_ID=0
 
 # --- Line crossing ---
+# Two horizontal counting lines:
+#   Line 1 (default ~33%): counts top-to-down (IN)
+#   Line 2 (default ~66%): counts bottom-to-up (OUT)
+# Fixed y-coordinate for line 1/IN (overrides LINE_Y1_FRAC if set)
 LINE_Y1=
-LINE_Y1_FRAC=0.70
+# Fraction of frame height for line 1 (default 0.33)
+LINE_Y1_FRAC=0.33
+# Fixed y-coordinate for line 2 (overrides LINE_Y2_FRAC if set)
 LINE_Y2=
-LINE_Y2_FRAC=0.30
+# Fraction of frame height for line 2 (default 0.66)
+LINE_Y2_FRAC=0.66
 
 # --- Counting day management ---
+# Daily cutoff time (HH:MM) – a new counting day starts after this time and the
+# previous day's counter_in / counter_out totals are finalized in the database.
+# CUTOFF_TIME is an alias used by the dashboard; DAILY_CUTOFF_TIME takes priority in counter_live_rknn.py.
 DAILY_CUTOFF_TIME=20:00
 CUTOFF_TIME=20:00
 
 # --- CSV export ---
-EXPORT_CSV=false
-CROSS_CSV=/opt/zenai-kpc-counter/crossings.csv
+# 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/crossings.csv
 
 # --- Crossing snapshots ---
-SAVE_CROSS_SNAPSHOT=true
+# Save an annotated frame image every time an object crosses a line and the
+# counter increases (true/false, default: false). Written to <DIR>/cross/
+# (filename: <YYYYmmdd_HHMMSS_mmm>_<in|out>_id<track>_f<frame>.jpg)
+SAVE_CROSS_SNAPSHOT=false
+# Also save one snapshot the first time each object is detected, before it crosses
+# (true/false, default: false). Written to <DIR>/detect/ with the same track id so
+# it can be correlated with the crossing snapshot
+# (filename: <YYYYmmdd_HHMMSS_mmm>_detect_id<track>_f<frame>.jpg)
 SAVE_DETECT_SNAPSHOT=false
-CROSS_SNAPSHOT_DIR=/opt/zenai-kpc-counter/snapshots
+# Base directory for snapshots (detect/ and cross/ subfolders are created inside).
+# The dashboard reads this same path to display the snapshot gallery, so keep it
+# identical for both the counter and the dashboard.
+CROSS_SNAPSHOT_DIR=/opt/batch-counter/snapshots
+# JPEG quality for snapshots (1-100)
 CROSS_SNAPSHOT_QUALITY=85
+# Retention: keep at most this many snapshot files (detect + cross combined);
+# oldest are deleted first (0 = unlimited)
 CROSS_SNAPSHOT_MAX_FILES=1000
-CROSS_SNAPSHOT_MAX_AGE_DAYS=3
-CROSS_SNAPSHOT_CLEANUP_SEC=3600
+# Retention: delete snapshots older than this many days (0 = never by age)
+CROSS_SNAPSHOT_MAX_AGE_DAYS=7
+# Run the cleanup sweep at most once every N seconds
+CROSS_SNAPSHOT_CLEANUP_SEC=60
 
 # --- Rate / performance ---
-MOTION_DETECTION_ENABLED=true
+# Enable motion detection pre-filter: skip inference on frames with no movement
+# (true/false, default: false), saving NPU/CPU load. Motion is measured by the
+# fraction of pixels that changed (localized-motion aware), NOT the whole-frame
+# average, so an object entering the edge of the frame is detected immediately.
+MOTION_DETECTION_ENABLED=false
+# Per-pixel intensity change (0-255) for a pixel to count as "moved". Lower = more
+# sensitive to subtle movement. Default 25.
 MOTION_PIXEL_DELTA=25
+# Fraction of frame pixels (0-1) that must change to trigger inference. Lower =
+# more sensitive / detects smaller or farther objects sooner. Default 0.002 (0.2%).
 MOTION_MIN_AREA_FRAC=0.002
+# Heartbeat: always run inference at least every N frames even with no detected
+# motion, so a slow or barely-moving object is never missed for long. Default 15.
 MOTION_HEARTBEAT_FRAMES=15
+# (Deprecated) old whole-frame mean-difference threshold; no longer used.
 MOTION_THRESHOLD=5.0
 
 # --- Runtime control (start/stop counting on the fly) ---
@@ -115,24 +186,41 @@ CONTROL_SOCKET_PORT=5090
 
 # 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
+# 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 ---
-LIVE_STREAM_ENABLED=true
-LIVE_STREAM_FRAME_PATH=/dev/shm/zenai-kpc-counter/live_frame.jpg
+# 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 counting-day JSON state file used by the dashboard
+CURRENT_COUNTER_PATH=/tmp/bytetrack_current_counter.json

counter_dashboard.py

@@ -48,28 +48,16 @@ DASHBOARD_PORT = int(os.getenv("DASHBOARD_PORT", "5000"))
 DASHBOARD_HOST = os.getenv("DASHBOARD_HOST", "0.0.0.0")
 FLASK_DEBUG = os.getenv("FLASK_DEBUG", "false").lower() == "true"
 
-_JPEG_SOI = b"\xff\xd8"
-_JPEG_EOI = b"\xff\xd9"
-_MIN_JPEG_BYTES = 128
-
-
-def _is_valid_jpeg(data):
-    return (
-        data
-        and len(data) >= _MIN_JPEG_BYTES
-        and data.startswith(_JPEG_SOI)
-        and data.endswith(_JPEG_EOI)
-    )
-
-
 @app.route("/api/live-video")
 def api_live_video():
+    if not os.path.isfile(LIVE_STREAM_FRAME_PATH):
+        return jsonify({"success": False, "error": "Live stream frame not available yet"}), 503
+
     def generate():
+        consecutive_fails = 0
+        MAX_FAILS = 30
         while True:
             try:
-                if not os.path.isfile(LIVE_STREAM_FRAME_PATH):
-                    time.sleep(0.5)
-                    continue
                 with open(LIVE_STREAM_FRAME_PATH, "rb") as f:
                     jpeg = f.read()
                 if not jpeg or len(jpeg) < 2 or jpeg[:2] != b"\xff\xd8":
@@ -82,10 +70,16 @@ def api_live_video():
                 yield (b"--frame\r\n"
                        b"Content-Type: image/jpeg\r\n\r\n" + jpeg + b"\r\n")
             except FileNotFoundError:
-                time.sleep(0.5)
+                consecutive_fails += 1
+                if consecutive_fails >= MAX_FAILS:
+                    return
+                time.sleep(1.0)
                 continue
             except Exception:
-                time.sleep(0.25)
+                consecutive_fails += 1
+                if consecutive_fails >= MAX_FAILS:
+                    return
+                time.sleep(0.5)
                 continue
             time.sleep(0.05)
     return Response(generate(), mimetype="multipart/x-mixed-replace; boundary=frame")
@@ -544,4 +538,4 @@ if __name__ == "__main__":
     print(f"Jetson counter dashboard at http://{DASHBOARD_HOST}:{DASHBOARD_PORT}")
     print(f"DB: {DB_PATH}")
     print(f"State: {CURRENT_COUNTER_PATH}")
-    app.run(host=DASHBOARD_HOST, port=DASHBOARD_PORT, debug=FLASK_DEBUG)
+    app.run(host=DASHBOARD_HOST, port=DASHBOARD_PORT, debug=FLASK_DEBUG)

counter_live_rknn.py

@@ -1108,18 +1108,6 @@ def draw_popups(img, popups, frame_idx):
     return alive
 
 
-def _write_live_frame_atomic(path, jpeg_bytes):
-    """Write JPEG atomically so dashboard readers never see a partial file."""
-    dest = Path(path)
-    dest.parent.mkdir(parents=True, exist_ok=True)
-    tmp = dest.with_suffix(dest.suffix + ".tmp")
-    with open(tmp, "wb") as f:
-        f.write(jpeg_bytes)
-        f.flush()
-        os.fsync(f.fileno())
-    os.replace(tmp, dest)
-
-
 def connect_stream(source, warmup=WARMUP_FRAMES):
     attempts = 0
     while not shutdown_requested:
@@ -1605,4 +1593,4 @@ object_tracked = {}
 
 
 if __name__ == "__main__":
-    run()
+    run()

env.example

@@ -1,32 +1,27 @@
-# =============================================================================
-# ZenAI KPC edge counter + dashboard
-# Shared config for: counter_live_rknn.py + counter_dashboard.py
-#
-# On device:
-#   cp env.example .env && nano .env
-#
-# Install path (systemd): /opt/zenai-kpc-python
-# Data path:               /opt/zenai-kpc-counter
-# See DEPLOY.md for full setup instructions.
+	# =============================================================================
+# 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 (video segments, default snapshot/CSV paths)
-OUTPUT_DIR=/opt/zenai-kpc-counter
-# SQLite database path for daily counter records
-DB_PATH=/opt/zenai-kpc-counter/counter.db
-# JSON file for the active counting-day state (counter writes, dashboard reads)
-STATE_FILE=/opt/zenai-kpc-counter/current_counter.json
+# Root output directory (logs, DB, video, CSV)
+OUTPUT_DIR=/opt/zenai-kpc-bt-counter
+# SQLite database path for daily counter records & crossing logs
+DB_PATH=/tmp/counter.db
+# JSON file persisting the current active counting day state
+STATE_FILE=/tmp/current_counter.json
 
 # --- Input source ---
 # RTSP / HTTP live stream, or a local video file path
-SOURCE=rtsp://user:pass@192.168.0.100:554/stream1
+#SOURCE=rtsp://user:pass@192.168.0.100:554/stream1
+SOURCE=rtsp://10.38.30.64:8554/my_stream
 # 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)
-MODEL_PATH=/opt/models/your_model.rknn
+# Path to exported .rknn model (YOLO format, e.g. yolo11n.rknn)
+MODEL_PATH=/opt/models/zenai_kac_sukawarna_20260702.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
@@ -58,24 +53,14 @@ TRACK_BUFFER=60
 # Minimum consecutive (or total) hits needed before a track is considered confirmed
 TRACK_MIN_HITS=3
 
-# --- ID-switch counting guards ---
-# Dedup guard: ignore a second crossing in the same direction within DEDUP_FRAMES
-# frames and DEDUP_PX horizontal pixels (set DEDUP_PX=-1 to disable).
-DEDUP_FRAMES=15
-DEDUP_PX=60
-# Inheritance guard: new tracks inherit position from a recently-seen nearby track
-# (set INHERIT_PX=-1 to disable).
-INHERIT_SEC=1.0
-INHERIT_PX=60
-
 # --- Display ---
-# Site name shown on the dashboard header
+# 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 grouping in the database
+# Label used for batch grouping in the database
 OBJECT_LABEL=karung
 # Class name for the counted object (must match model class order)
 CLASS_OBJECT=karung
@@ -83,59 +68,83 @@ CLASS_OBJECT=karung
 OBJECT_CLASS_ID=0
 
 # --- Line crossing ---
-# Line 1 (~upper): counts top-to-down (IN). Line 2 (~lower): bottom-to-up (OUT).
-# Fixed y-coordinate overrides the fraction if set.
+# Two horizontal counting lines:
+#   Line 1 (default ~33%): counts top-to-down (IN)
+#   Line 2 (default ~66%): counts bottom-to-up (OUT)
+# Fixed y-coordinate for line 1/IN (overrides LINE_Y1_FRAC if set)
 LINE_Y1=
+# Fraction of frame height for line 1 (default 0.33)
 LINE_Y1_FRAC=0.70
+# Fixed y-coordinate for line 2 (overrides LINE_Y2_FRAC if set)
 LINE_Y2=
+# Fraction of frame height for line 2 (default 0.66)
 LINE_Y2_FRAC=0.30
 
 # --- Counting day management ---
-# New counting day starts after this time (HH:MM).
+# Daily cutoff time (HH:MM) – a new counting day starts after this time and the
+# previous day's counter_in / counter_out totals are finalized in the database.
+# CUTOFF_TIME is an alias used by the dashboard; DAILY_CUTOFF_TIME takes priority in counter_live_rknn.py.
 DAILY_CUTOFF_TIME=20:00
 CUTOFF_TIME=20:00
 
 # --- CSV export ---
+# Write per-crossing events to a CSV file (true/false)
 EXPORT_CSV=false
-CROSS_CSV=/opt/zenai-kpc-counter/crossings.csv
-
-# --- Crossing snapshots ---
-SAVE_CROSS_SNAPSHOT=true
-SAVE_DETECT_SNAPSHOT=false
-CROSS_SNAPSHOT_DIR=/opt/zenai-kpc-counter/snapshots
-CROSS_SNAPSHOT_QUALITY=85
-CROSS_SNAPSHOT_MAX_FILES=1000
-CROSS_SNAPSHOT_MAX_AGE_DAYS=3
-CROSS_SNAPSHOT_CLEANUP_SEC=3600
+# Path where the crossing CSV is written
+CROSS_CSV=/tmp/crossings.csv
 
 # --- Rate / performance ---
+# Enable motion detection pre-filter: skip inference on frames with no movement
+# (true/false, default: false). When enabled, frames below MOTION_THRESHOLD are
+# skipped, saving NPU/CPU load.
 MOTION_DETECTION_ENABLED=true
-MOTION_PIXEL_DELTA=25
-MOTION_MIN_AREA_FRAC=0.002
-MOTION_HEARTBEAT_FRAMES=15
+# Mean absolute pixel difference threshold (0–255) to consider a frame as having
+# motion. Lower = more sensitive. Default 5.0.
 MOTION_THRESHOLD=5.0
+# 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
+# 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=true
-LIVE_STREAM_FRAME_PATH=/dev/shm/zenai-kpc-counter/live_frame.jpg
+# 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 counting-day JSON state file used by the dashboard
+CURRENT_COUNTER_PATH=/tmp/bytetrack_current_counter.json
 
-# Debug: set DEBUG_TRACKING=true to log per-frame tracking details to stdout
-# DEBUG_TRACKING=false
+SAVE_CROSS_SNAPSHOT=true
+CROSS_SNAPSHOT_DIR=/opt/zenai-kpc-snaps/snapshots
+CROSS_SNAPSHOT_CLEANUP_SEC=3600
+CROSS_SNAPSHOT_MAX_AGE_DAYS=3
+
+DEDUP_PX=-1

templates/dashboard.html

@@ -814,9 +814,6 @@ function updateToggleIcon() {
 let mainChart = null;
 let videoActive = false;
 let videoErrorTimer = null;
-let videoWatchdogTimer = null;
-let lastVideoFrameAt = 0;
-const VIDEO_STALL_MS = 8000;
 
 document.addEventListener('DOMContentLoaded', () => {
   loadSummary();
@@ -1140,32 +1137,6 @@ document.addEventListener('keydown', (e) => {
 
 // --- Live Video Feed ---
 
-function reconnectVideo() {
-  if (!videoActive) return;
-  const img = document.getElementById('live-video-img');
-  if (!img) return;
-  lastVideoFrameAt = Date.now();
-  img.src = '/api/live-video?' + Date.now();
-}
-
-function startVideoWatchdog() {
-  stopVideoWatchdog();
-  lastVideoFrameAt = Date.now();
-  videoWatchdogTimer = setInterval(() => {
-    if (!videoActive) return;
-    if (Date.now() - lastVideoFrameAt > VIDEO_STALL_MS) {
-      reconnectVideo();
-    }
-  }, 2000);
-}
-
-function stopVideoWatchdog() {
-  if (videoWatchdogTimer) {
-    clearInterval(videoWatchdogTimer);
-    videoWatchdogTimer = null;
-  }
-}
-
 function toggleVideo() {
   const btn = document.getElementById('videoToggle');
   const img = document.getElementById('live-video-img');
@@ -1176,16 +1147,14 @@ function toggleVideo() {
 
   if (videoActive) {
     resetFilter();
+    img.src = '/api/live-video?' + Date.now();
     img.style.display = 'block';
     if (placeholder) placeholder.style.display = 'none';
     btn.textContent = 'STREAM ON';
     btn.classList.add('active');
     status.innerHTML = '<span style="width:6px;height:6px;border-radius:50%;background:var(--accent4);animation:blink 1.5s ease-in-out infinite;"></span> connecting...';
     status.className = 'video-status waiting';
-    reconnectVideo();
-    startVideoWatchdog();
   } else {
-    stopVideoWatchdog();
     img.src = '';
     img.style.display = 'none';
     if (placeholder) placeholder.style.display = '';
@@ -1198,7 +1167,6 @@ function toggleVideo() {
 }
 
 function onVideoLoad() {
-  lastVideoFrameAt = Date.now();
   const status = document.getElementById('video-status');
   status.innerHTML = '<span style="width:6px;height:6px;border-radius:50%;background:var(--accent4);box-shadow:0 0 6px var(--accent4);animation:blink 1.5s ease-in-out infinite;"></span> live';
   status.className = 'video-status connected';
@@ -1210,7 +1178,10 @@ function onVideoError() {
   if (overlay) overlay.classList.add('visible');
   if (videoErrorTimer) clearTimeout(videoErrorTimer);
   videoErrorTimer = setTimeout(() => {
-    reconnectVideo();
+    if (videoActive) {
+      const img = document.getElementById('live-video-img');
+      img.src = '/api/live-video?' + Date.now();
+    }
   }, 2000);
 }
 
@@ -1246,4 +1217,4 @@ function hideVideoError() {
 </script>
 
 </body>
-</html>
+</html>