diff --git a/DEPLOY.md b/DEPLOY.md new file mode 100644 index 0000000..044133d --- /dev/null +++ b/DEPLOY.md @@ -0,0 +1,239 @@ +# ZenAI KPC Counter — Edge Deployment Guide + +Production deployment for **RK3588** (or compatible RKNN NPU) edge devices running: + +| Component | Script | systemd unit | +|-----------|--------|--------------| +| RTSP counter (RKNN + ByteTrack) | `counter_live_rknn.py` | `zenai-kpc-counter.service` | +| Web dashboard (Flask) | `counter_dashboard.py` | `zenai-kpc-dashboard.service` | + +Both processes share a single `.env` file and read/write the same SQLite database and state JSON. + +--- + +## 1. Prerequisites + +### Hardware & OS + +- RK3588 board (or Jetson/RK device with RKNN Lite runtime) +- Linux with systemd +- Network access to the RTSP camera stream + +### System packages + +```bash +sudo apt update +sudo apt install -y python3 python3-venv python3-pip ffmpeg libgl1 +``` + +`ffmpeg` is required for low-latency RTSP capture via OpenCV. `libgl1` is often needed for `opencv-python` on headless systems. + +### RKNN model + +Export or copy your `.rknn` model to the device, e.g.: + +```text +/opt/models/your_model.rknn +``` + +Set `MODEL_PATH` in `.env` to match. The model class count must match `NUM_CLASSES`, and `OBJECT_CLASS_ID` must point at the class you count. + +--- + +## 2. Directory layout + +Default paths used by the service files and `env.example`: + +```text +/opt/zenai-kpc-python/ # application code (this repo) +├── counter_live_rknn.py +├── counter_dashboard.py +├── counter_store.py +├── templates/ +├── venv/ # Python virtual environment (created during install) +├── .env # runtime config (not in git) +├── env.example # template — copy to .env +└── DEPLOY.md + +/opt/zenai-kpc-counter/ # persistent runtime data (created automatically) +├── counter.db # SQLite daily records +├── current_counter.json # live counting-day state +├── snapshots/ # crossing/detect JPEGs (if enabled) +└── crossings.csv # optional per-event CSV + +/opt/models/ # RKNN models (deploy separately) +/dev/shm/zenai-kpc-counter/ # live JPEG frame for dashboard video (tmpfs) +``` + +--- + +## 3. Install application + +### 3.1 Copy code to the device + +```bash +sudo mkdir -p /opt/zenai-kpc-python +sudo rsync -av --exclude venv --exclude .env --exclude __pycache__ \ + ./ /opt/zenai-kpc-python/ +# Or: sudo git clone /opt/zenai-kpc-python +``` + +### 3.2 Create virtual environment and install dependencies + +```bash +cd /opt/zenai-kpc-python +sudo python3 -m venv venv +sudo ./venv/bin/pip install --upgrade pip +sudo ./venv/bin/pip install -r requirements.txt +``` + +> `rknn-toolkit-lite2` is platform-specific. Install on the target ARM device, not on a Windows dev machine. + +### 3.3 Create runtime config + +```bash +cd /opt/zenai-kpc-python +sudo cp env.example .env +sudo nano .env +``` + +**Minimum values to edit before starting:** + +| Variable | Description | +|----------|-------------| +| `SOURCE` | RTSP URL or local video file path | +| `MODEL_PATH` | Path to your `.rknn` model on device | +| `NUM_CLASSES` | Must match the exported model | +| `OBJECT_CLASS_ID` | Class index of the object being counted | +| `CLASS_OBJECT` / `OBJECT_LABEL` | Labels stored in DB (e.g. `karung`) | +| `LINE_Y1_FRAC` / `LINE_Y2_FRAC` | Counting line positions (tune per camera) | +| `SECRET_KEY` | Random string for Flask sessions | + +Ensure `STATE_FILE` and `DB_PATH` both live under `/opt/zenai-kpc-counter/` so data survives reboots (avoid `/tmp` in production). + +### 3.4 Create data directories (optional — app creates most paths automatically) + +```bash +sudo mkdir -p /opt/zenai-kpc-counter /opt/models /dev/shm/zenai-kpc-counter +``` + +--- + +## 4. Install systemd services + +```bash +cd /opt/zenai-kpc-python +sudo cp zenai-kpc-counter.service zenai-kpc-dashboard.service /etc/systemd/system/ +sudo systemctl daemon-reload +sudo systemctl enable zenai-kpc-counter zenai-kpc-dashboard +sudo systemctl start zenai-kpc-counter +sudo systemctl start zenai-kpc-dashboard +``` + +The dashboard unit starts **after** the counter unit (`After=zenai-kpc-counter.service`). + +### Verify + +```bash +systemctl status zenai-kpc-counter +systemctl status zenai-kpc-dashboard +journalctl -u zenai-kpc-counter -f +``` + +Open the dashboard in a browser: + +```text +http://:5000 +``` + +(Port is set by `DASHBOARD_PORT` in `.env`, default `5000`.) + +--- + +## 5. Operations + +### Restart after config change + +```bash +sudo systemctl restart zenai-kpc-counter +sudo systemctl restart zenai-kpc-dashboard +``` + +### View logs + +```bash +journalctl -u zenai-kpc-counter -n 100 --no-pager +journalctl -u zenai-kpc-dashboard -n 100 --no-pager +``` + +### Stop services + +```bash +sudo systemctl stop zenai-kpc-dashboard zenai-kpc-counter +``` + +The counter handles `SIGTERM` gracefully — it finishes the current frame, persists state to SQLite, then exits. + +### Update application code + +```bash +cd /opt/zenai-kpc-python +sudo systemctl stop zenai-kpc-dashboard zenai-kpc-counter +# rsync or git pull new code +sudo ./venv/bin/pip install -r requirements.txt # if dependencies changed +sudo systemctl start zenai-kpc-counter zenai-kpc-dashboard +``` + +--- + +## 6. Troubleshooting + +| Symptom | Things to check | +|---------|-----------------| +| Counter won't start | `journalctl -u zenai-kpc-counter`; verify `MODEL_PATH` exists; RKNN drivers installed | +| No RTSP frames | Ping camera; test with `ffplay `; check `OPENCV_FFMPEG_CAPTURE_OPTIONS` | +| Dashboard shows 0 count | `STATE_FILE` in `.env` must match between counter and dashboard; check file exists | +| Live video blank | `LIVE_STREAM_ENABLED=true`; path matches `LIVE_STREAM_FRAME_PATH` in both processes | +| Wrong counts | Tune `LINE_Y1_FRAC`/`LINE_Y2_FRAC`, `CONF`, ByteTrack thresholds; enable `DEBUG_TRACKING=true` temporarily | +| Service keeps restarting | `journalctl -u zenai-kpc-counter -e`; often missing model, bad RTSP URL, or venv not created | + +### Manual test (without systemd) + +```bash +cd /opt/zenai-kpc-python +source venv/bin/activate +python counter_live_rknn.py # terminal 1 +python counter_dashboard.py # terminal 2 +``` + +--- + +## 7. Optional: reverse proxy + +For HTTPS or port 80 access, put nginx in front of the dashboard: + +```nginx +server { + listen 80; + server_name counter.example.com; + + location / { + proxy_pass http://127.0.0.1:5000; + proxy_http_version 1.1; + proxy_set_header Host $host; + proxy_set_header X-Real-IP $remote_addr; + proxy_buffering off; # needed for /api/live-video MJPEG stream + } +} +``` + +The live JPEG at `LIVE_STREAM_FRAME_PATH` can also be served statically by nginx if you prefer not to use the Flask MJPEG endpoint. + +--- + +## 8. Security notes + +- Change `SECRET_KEY` from the default before exposing the dashboard on a network. +- Services currently run as `root` for simplicity on edge devices. For hardened deployments, create a dedicated user, chown `/opt/zenai-kpc-counter`, and update the `User=` / `Group=` lines in the service files. +- Do not commit `.env` — it may contain RTSP credentials. +- Set `FLASK_DEBUG=false` in production. diff --git a/config.env.example b/config.env.example index d5423b2..9ede88b 100644 --- a/config.env.example +++ b/config.env.example @@ -1,195 +1,105 @@ # ============================================================================= -# 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 +# 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. # ============================================================================= # --- Core paths --- -# 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 +OUTPUT_DIR=/opt/zenai-kpc-counter +DB_PATH=/opt/zenai-kpc-counter/counter.db +STATE_FILE=/opt/zenai-kpc-counter/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 --- -# 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) +MODEL_PATH=/opt/models/your_model.rknn 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) +CORE_MASK=1 DEVICE=0 # --- YOLO decoder --- -# 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 +NUM_CLASSES=4 SCORE_SIGMOID=false # --- Detection --- -# Confidence threshold – detections below this are discarded before NMS -CONF=0.3 +CONF=0.5 # --- ByteTrack tracking --- -# Detections with score >= this get priority matching in the first association stage TRACK_HIGH_THRESH=0.5 -# 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_LOW_THRESH=0.3 +TRACK_MATCH_THRESH=0.7 +TRACK_BUFFER=60 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 -# 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_LABEL=karung +CLASS_OBJECT=karung 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= -# 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_Y1_FRAC=0.70 LINE_Y2= -# Fraction of frame height for line 2 (default 0.66) -LINE_Y2_FRAC=0.66 +LINE_Y2_FRAC=0.30 # --- 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 --- -# 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 +EXPORT_CSV=false +CROSS_CSV=/opt/zenai-kpc-counter/crossings.csv # --- Crossing snapshots --- -# 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_CROSS_SNAPSHOT=true SAVE_DETECT_SNAPSHOT=false -# 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_DIR=/opt/zenai-kpc-counter/snapshots 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 -# 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 +CROSS_SNAPSHOT_MAX_AGE_DAYS=3 +CROSS_SNAPSHOT_CLEANUP_SEC=3600 # --- Rate / performance --- -# 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_DETECTION_ENABLED=true 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 -# 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=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_ENABLED=true +LIVE_STREAM_FRAME_PATH=/dev/shm/zenai-kpc-counter/live_frame.jpg 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 diff --git a/env.example b/env.example index f2164da..bf4ef20 100644 --- a/env.example +++ b/env.example @@ -1,27 +1,32 @@ # ============================================================================= -# 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 +# 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. # ============================================================================= # --- Core paths --- -# 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 +# 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 # --- Input source --- # RTSP / HTTP live stream, or a local video file path -#SOURCE=rtsp://user:pass@192.168.0.100:554/stream1 -SOURCE=rtsp://10.38.30.64:8554/my_stream +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/zenai_kac_sukawarna_20260702.rknn +# Path to exported .rknn model (YOLO format) +MODEL_PATH=/opt/models/your_model.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 @@ -53,14 +58,24 @@ 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 (top-right) +# Site name shown on the dashboard header 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 +# Label used for grouping in the database OBJECT_LABEL=karung # Class name for the counted object (must match model class order) CLASS_OBJECT=karung @@ -68,83 +83,59 @@ CLASS_OBJECT=karung 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 1 (~upper): counts top-to-down (IN). Line 2 (~lower): bottom-to-up (OUT). +# Fixed y-coordinate overrides the fraction 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 --- -# 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. +# New counting day starts after this time (HH:MM). DAILY_CUTOFF_TIME=20:00 CUTOFF_TIME=20:00 # --- CSV export --- -# Write per-crossing events to a CSV file (true/false) EXPORT_CSV=false -# Path where the crossing CSV is written -CROSS_CSV=/tmp/crossings.csv +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 # --- 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 -# Mean absolute pixel difference threshold (0–255) to consider a frame as having -# motion. Lower = more sensitive. Default 5.0. +MOTION_PIXEL_DELTA=25 +MOTION_MIN_AREA_FRAC=0.002 +MOTION_HEARTBEAT_FRAMES=15 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 -# 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_FRAME_PATH=/dev/shm/zenai-kpc-counter/live_frame.jpg 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 -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 +# Debug: set DEBUG_TRACKING=true to log per-frame tracking details to stdout +# DEBUG_TRACKING=false diff --git a/zenai-kpc-counter.service b/zenai-kpc-counter.service new file mode 100644 index 0000000..c4e92a2 --- /dev/null +++ b/zenai-kpc-counter.service @@ -0,0 +1,32 @@ +[Unit] +Description=ZenAI KPC Edge Counter (RTSP + RKNN) +Documentation=file:///opt/zenai-kpc-python/DEPLOY.md +After=network-online.target +Wants=network-online.target + +[Service] +Type=simple +User=root +Group=root + +WorkingDirectory=/opt/zenai-kpc-python +EnvironmentFile=/opt/zenai-kpc-python/.env +Environment=PYTHONNOUSERSITE=1 +Environment=PATH=/opt/zenai-kpc-python/venv/bin:/usr/local/bin:/usr/bin:/bin + +ExecStart=/opt/zenai-kpc-python/venv/bin/python counter_live_rknn.py + +TimeoutStopSec=30 +KillSignal=SIGTERM + +Restart=always +RestartSec=10 +StartLimitInterval=120s +StartLimitBurst=5 + +NoNewPrivileges=true +ProtectHome=true +PrivateTmp=false + +[Install] +WantedBy=multi-user.target diff --git a/zenai-kpc-dashboard.service b/zenai-kpc-dashboard.service new file mode 100644 index 0000000..1b5cc13 --- /dev/null +++ b/zenai-kpc-dashboard.service @@ -0,0 +1,32 @@ +[Unit] +Description=ZenAI KPC Dashboard (Flask) +Documentation=file:///opt/zenai-kpc-python/DEPLOY.md +After=network-online.target zenai-kpc-counter.service +Wants=network-online.target + +[Service] +Type=simple +User=root +Group=root + +WorkingDirectory=/opt/zenai-kpc-python +EnvironmentFile=/opt/zenai-kpc-python/.env +Environment=PATH=/opt/zenai-kpc-python/venv/bin:/usr/local/bin:/usr/bin:/bin +Environment=FLASK_DEBUG=false + +ExecStart=/opt/zenai-kpc-python/venv/bin/python counter_dashboard.py + +TimeoutStopSec=15 +KillSignal=SIGTERM + +Restart=always +RestartSec=5 +StartLimitInterval=60s +StartLimitBurst=3 + +NoNewPrivileges=true +ProtectHome=true +PrivateTmp=false + +[Install] +WantedBy=multi-user.target