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 <repo-url> /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://<device-ip>: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 <SOURCE>`; 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.

config.env.example

@@ -1,195 +1,105 @@
 # =============================================================================
-# Edge RK3588 production counter + dashboard
+# DEPRECATED — use env.example instead.
-# Shared config for: counter_live_rknn_bytetrack.py + counter_dashboard.py
+#
-# Copy to .env on device:  cp config.env.example .env && nano .env
+#   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/zenai-kpc-counter
-OUTPUT_DIR=/opt/bytetrack-counter
+DB_PATH=/opt/zenai-kpc-counter/counter.db
-# SQLite database path for daily counter records & crossing logs
+STATE_FILE=/opt/zenai-kpc-counter/current_counter.json
-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 ---
-# Path to exported .rknn model (YOLO format, e.g. yolo11n.rknn)
+MODEL_PATH=/opt/models/your_model.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=1
-CORE_MASK=7
-# Compute device index (reserved; not used at runtime)
 DEVICE=0
 
 # --- YOLO decoder ---
-# Number of object classes the model outputs
+NUM_CLASSES=4
-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=0.5
-CONF=0.3
 
 # --- 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=0.3
-TRACK_LOW_THRESH=0.1
+TRACK_MATCH_THRESH=0.7
-# IoU threshold for the first-stage association (0–1). Higher = stricter overlap required
+TRACK_BUFFER=60
-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
-# Label used for batch grouping in the database
+OBJECT_LABEL=karung
-OBJECT_LABEL=object
+CLASS_OBJECT=karung
-# 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=
-# Fraction of frame height for line 1 (default 0.33)
+LINE_Y1_FRAC=0.70
-LINE_Y1_FRAC=0.33
-# 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
-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 ---
-# Write per-crossing events to a CSV file (true/false)
+EXPORT_CSV=false
-EXPORT_CSV=true
+CROSS_CSV=/opt/zenai-kpc-counter/crossings.csv
-# Path where the crossing CSV is written
-CROSS_CSV=/opt/batch-counter/crossings.csv
 
 # --- Crossing snapshots ---
-# Save an annotated frame image every time an object crosses a line and the
+SAVE_CROSS_SNAPSHOT=true
-# 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
-# Base directory for snapshots (detect/ and cross/ subfolders are created inside).
+CROSS_SNAPSHOT_DIR=/opt/zenai-kpc-counter/snapshots
-# 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
-# Retention: delete snapshots older than this many days (0 = never by age)
+CROSS_SNAPSHOT_MAX_AGE_DAYS=3
-CROSS_SNAPSHOT_MAX_AGE_DAYS=7
+CROSS_SNAPSHOT_CLEANUP_SEC=3600
-# Run the cleanup sweep at most once every N seconds
-CROSS_SNAPSHOT_CLEANUP_SEC=60
 
 # --- Rate / performance ---
-# Enable motion detection pre-filter: skip inference on frames with no movement
+MOTION_DETECTION_ENABLED=true
-# (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
-# 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_ENABLED=false
+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

env.example

@@ -1,27 +1,32 @@
 # =============================================================================
-# Edge RK3588 production counter + dashboard
+# ZenAI KPC edge counter + dashboard
-# Shared config for: counter_live_rknn_bytetrack.py + counter_dashboard.py
+# Shared config for: counter_live_rknn.py + counter_dashboard.py
-# Copy to .env on device:  cp config.env.example .env && nano .env
+#
+# 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)
+# Root output directory (video segments, default snapshot/CSV paths)
-OUTPUT_DIR=/opt/zenai-kpc-bt-counter
+OUTPUT_DIR=/opt/zenai-kpc-counter
-# SQLite database path for daily counter records & crossing logs
+# SQLite database path for daily counter records
-DB_PATH=/tmp/counter.db
+DB_PATH=/opt/zenai-kpc-counter/counter.db
-# JSON file persisting the current active counting day state
+# JSON file for the active counting-day state (counter writes, dashboard reads)
-STATE_FILE=/tmp/current_counter.json
+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://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, e.g. yolo11n.rknn)
+# Path to exported .rknn model (YOLO format)
-MODEL_PATH=/opt/models/zenai_kac_sukawarna_20260702.rknn
+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 (~upper): counts top-to-down (IN). Line 2 (~lower): bottom-to-up (OUT).
-#   Line 1 (default ~33%): counts top-to-down (IN)
+# Fixed y-coordinate overrides the fraction if set.
-#   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 ---
-# Daily cutoff time (HH:MM) – a new counting day starts after this time and the
+# New counting day starts after this time (HH:MM).
-# 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
-# Path where the crossing CSV is written
+CROSS_CSV=/opt/zenai-kpc-counter/crossings.csv
-CROSS_CSV=/tmp/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_PIXEL_DELTA=25
-# motion. Lower = more sensitive. Default 5.0.
+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/zenai-kpc-counter/live_frame.jpg
-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
 
-SAVE_CROSS_SNAPSHOT=true
+# Debug: set DEBUG_TRACKING=true to log per-frame tracking details to stdout
-CROSS_SNAPSHOT_DIR=/opt/zenai-kpc-snaps/snapshots
+# DEBUG_TRACKING=false
-CROSS_SNAPSHOT_CLEANUP_SEC=3600
-CROSS_SNAPSHOT_MAX_AGE_DAYS=3
-
-DEDUP_PX=-1

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

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