diff --git a/config.env.example b/config.env.example index ca08cf3..6b4bb92 100644 --- a/config.env.example +++ b/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 /cross/ +# (filename: __id_f.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 /detect/ with the same track id so +# it can be correlated with the crossing snapshot +# (filename: _detect_id_f.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 \ No newline at end of file diff --git a/counter_dashboard.py b/counter_dashboard.py index 7fa6525..c645346 100644 --- a/counter_dashboard.py +++ b/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) \ No newline at end of file diff --git a/counter_live_rknn.py b/counter_live_rknn.py index b9082b2..4f8f0e0 100644 --- a/counter_live_rknn.py +++ b/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() \ No newline at end of file diff --git a/env.example b/env.example index bf4ef20..d0db80e 100644 --- a/env.example +++ b/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 \ No newline at end of file diff --git a/templates/dashboard.html b/templates/dashboard.html index 46e8261..23640bd 100644 --- a/templates/dashboard.html +++ b/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 = ' 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 = ' 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() { - + \ No newline at end of file