Merging for deployment update with service #2
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# ZenAI KPC Counter — Edge Deployment Guide
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Production deployment for **RK3588** (or compatible RKNN NPU) edge devices running:
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| Component | Script | systemd unit |
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|-----------|--------|--------------|
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| RTSP counter (RKNN + ByteTrack) | `counter_live_rknn.py` | `zenai-kpc-counter.service` |
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| Web dashboard (Flask) | `counter_dashboard.py` | `zenai-kpc-dashboard.service` |
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Both processes share a single `.env` file and read/write the same SQLite database and state JSON.
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---
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## 1. Prerequisites
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### Hardware & OS
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- RK3588 board (or Jetson/RK device with RKNN Lite runtime)
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- Linux with systemd
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- Network access to the RTSP camera stream
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### System packages
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```bash
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sudo apt update
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sudo apt install -y python3 python3-venv python3-pip ffmpeg libgl1
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```
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`ffmpeg` is required for low-latency RTSP capture via OpenCV. `libgl1` is often needed for `opencv-python` on headless systems.
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### RKNN model
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Export or copy your `.rknn` model to the device, e.g.:
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```text
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/opt/models/your_model.rknn
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```
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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.
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---
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## 2. Directory layout
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Default paths used by the service files and `env.example`:
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```text
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/opt/zenai-kpc-python/ # application code (this repo)
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├── counter_live_rknn.py
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├── counter_dashboard.py
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├── counter_store.py
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├── templates/
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├── venv/ # Python virtual environment (created during install)
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├── .env # runtime config (not in git)
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├── env.example # template — copy to .env
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└── DEPLOY.md
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/opt/zenai-kpc-counter/ # persistent runtime data (created automatically)
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├── counter.db # SQLite daily records
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├── current_counter.json # live counting-day state
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├── snapshots/ # crossing/detect JPEGs (if enabled)
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└── crossings.csv # optional per-event CSV
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/opt/models/ # RKNN models (deploy separately)
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/dev/shm/zenai-kpc-counter/ # live JPEG frame for dashboard video (tmpfs)
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```
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---
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## 3. Install application
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### 3.1 Copy code to the device
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```bash
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sudo mkdir -p /opt/zenai-kpc-python
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sudo rsync -av --exclude venv --exclude .env --exclude __pycache__ \
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./ /opt/zenai-kpc-python/
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# Or: sudo git clone <repo-url> /opt/zenai-kpc-python
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```
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### 3.2 Create virtual environment and install dependencies
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```bash
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cd /opt/zenai-kpc-python
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sudo python3 -m venv venv
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sudo ./venv/bin/pip install --upgrade pip
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sudo ./venv/bin/pip install -r requirements.txt
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```
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> `rknn-toolkit-lite2` is platform-specific. Install on the target ARM device, not on a Windows dev machine.
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### 3.3 Create runtime config
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```bash
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cd /opt/zenai-kpc-python
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sudo cp env.example .env
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sudo nano .env
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```
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**Minimum values to edit before starting:**
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| Variable | Description |
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|----------|-------------|
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| `SOURCE` | RTSP URL or local video file path |
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| `MODEL_PATH` | Path to your `.rknn` model on device |
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| `NUM_CLASSES` | Must match the exported model |
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| `OBJECT_CLASS_ID` | Class index of the object being counted |
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| `CLASS_OBJECT` / `OBJECT_LABEL` | Labels stored in DB (e.g. `karung`) |
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| `LINE_Y1_FRAC` / `LINE_Y2_FRAC` | Counting line positions (tune per camera) |
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| `SECRET_KEY` | Random string for Flask sessions |
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Ensure `STATE_FILE` and `DB_PATH` both live under `/opt/zenai-kpc-counter/` so data survives reboots (avoid `/tmp` in production).
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### 3.4 Create data directories (optional — app creates most paths automatically)
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```bash
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sudo mkdir -p /opt/zenai-kpc-counter /opt/models /dev/shm/zenai-kpc-counter
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```
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---
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## 4. Install systemd services
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```bash
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cd /opt/zenai-kpc-python
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sudo cp zenai-kpc-counter.service zenai-kpc-dashboard.service /etc/systemd/system/
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sudo systemctl daemon-reload
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sudo systemctl enable zenai-kpc-counter zenai-kpc-dashboard
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sudo systemctl start zenai-kpc-counter
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sudo systemctl start zenai-kpc-dashboard
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```
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The dashboard unit starts **after** the counter unit (`After=zenai-kpc-counter.service`).
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### Verify
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```bash
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systemctl status zenai-kpc-counter
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systemctl status zenai-kpc-dashboard
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journalctl -u zenai-kpc-counter -f
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```
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Open the dashboard in a browser:
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```text
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http://<device-ip>:5000
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```
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(Port is set by `DASHBOARD_PORT` in `.env`, default `5000`.)
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---
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## 5. Operations
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### Restart after config change
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```bash
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sudo systemctl restart zenai-kpc-counter
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sudo systemctl restart zenai-kpc-dashboard
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```
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### View logs
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```bash
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journalctl -u zenai-kpc-counter -n 100 --no-pager
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journalctl -u zenai-kpc-dashboard -n 100 --no-pager
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```
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### Stop services
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```bash
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sudo systemctl stop zenai-kpc-dashboard zenai-kpc-counter
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```
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The counter handles `SIGTERM` gracefully — it finishes the current frame, persists state to SQLite, then exits.
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### Update application code
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```bash
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cd /opt/zenai-kpc-python
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sudo systemctl stop zenai-kpc-dashboard zenai-kpc-counter
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# rsync or git pull new code
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sudo ./venv/bin/pip install -r requirements.txt # if dependencies changed
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sudo systemctl start zenai-kpc-counter zenai-kpc-dashboard
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```
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---
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## 6. Troubleshooting
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| Symptom | Things to check |
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|---------|-----------------|
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| Counter won't start | `journalctl -u zenai-kpc-counter`; verify `MODEL_PATH` exists; RKNN drivers installed |
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| No RTSP frames | Ping camera; test with `ffplay <SOURCE>`; check `OPENCV_FFMPEG_CAPTURE_OPTIONS` |
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| Dashboard shows 0 count | `STATE_FILE` in `.env` must match between counter and dashboard; check file exists |
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| Live video blank | `LIVE_STREAM_ENABLED=true`; path matches `LIVE_STREAM_FRAME_PATH` in both processes; if using nginx, set `proxy_read_timeout` (see §7) |
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| Wrong counts | Tune `LINE_Y1_FRAC`/`LINE_Y2_FRAC`, `CONF`, ByteTrack thresholds; enable `DEBUG_TRACKING=true` temporarily |
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| Service keeps restarting | `journalctl -u zenai-kpc-counter -e`; often missing model, bad RTSP URL, or venv not created |
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### Manual test (without systemd)
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```bash
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cd /opt/zenai-kpc-python
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source venv/bin/activate
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python counter_live_rknn.py # terminal 1
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python counter_dashboard.py # terminal 2
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```
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---
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## 7. Optional: reverse proxy
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For HTTPS or port 80 access, put nginx in front of the dashboard:
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```nginx
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server {
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listen 80;
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server_name counter.example.com;
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location / {
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proxy_pass http://127.0.0.1:5000;
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proxy_http_version 1.1;
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proxy_set_header Host $host;
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proxy_set_header X-Real-IP $remote_addr;
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proxy_buffering off; # required for /api/live-video MJPEG stream
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proxy_read_timeout 3600s; # keep long-lived MJPEG connections open
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proxy_send_timeout 3600s;
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}
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}
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```
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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.
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---
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## 8. Security notes
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- Change `SECRET_KEY` from the default before exposing the dashboard on a network.
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- 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.
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- Do not commit `.env` — it may contain RTSP credentials.
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- Set `FLASK_DEBUG=false` in production.
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+1
-1
@@ -223,4 +223,4 @@ DASHBOARD_PORT=5000
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# Enable Flask debug mode (true/false) — auto-reloads on code changes; disable in production
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# Enable Flask debug mode (true/false) — auto-reloads on code changes; disable in production
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FLASK_DEBUG=false
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FLASK_DEBUG=false
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# Fallback name for the active counting-day JSON state file used by the dashboard
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# Fallback name for the active counting-day JSON state file used by the dashboard
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CURRENT_COUNTER_PATH=/tmp/bytetrack_current_counter.json
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CURRENT_COUNTER_PATH=/tmp/bytetrack_current_counter.json
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@@ -538,4 +538,4 @@ if __name__ == "__main__":
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print(f"Jetson counter dashboard at http://{DASHBOARD_HOST}:{DASHBOARD_PORT}")
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print(f"Jetson counter dashboard at http://{DASHBOARD_HOST}:{DASHBOARD_PORT}")
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print(f"DB: {DB_PATH}")
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print(f"DB: {DB_PATH}")
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print(f"State: {CURRENT_COUNTER_PATH}")
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print(f"State: {CURRENT_COUNTER_PATH}")
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app.run(host=DASHBOARD_HOST, port=DASHBOARD_PORT, debug=FLASK_DEBUG)
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app.run(host=DASHBOARD_HOST, port=DASHBOARD_PORT, debug=FLASK_DEBUG)
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@@ -1593,4 +1593,4 @@ object_tracked = {}
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if __name__ == "__main__":
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if __name__ == "__main__":
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run()
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run()
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+1
-1
@@ -147,4 +147,4 @@ CROSS_SNAPSHOT_DIR=/opt/zenai-kpc-snaps/snapshots
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CROSS_SNAPSHOT_CLEANUP_SEC=3600
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CROSS_SNAPSHOT_CLEANUP_SEC=3600
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CROSS_SNAPSHOT_MAX_AGE_DAYS=3
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CROSS_SNAPSHOT_MAX_AGE_DAYS=3
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DEDUP_PX=-1
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DEDUP_PX=-1
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@@ -1217,4 +1217,4 @@ function hideVideoError() {
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</script>
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</script>
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</body>
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</body>
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</html>
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</html>
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[Unit]
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Description=ZenAI KPC Edge Counter (RTSP + RKNN)
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Documentation=file:///opt/zenai-kpc-python/DEPLOY.md
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After=network-online.target
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Wants=network-online.target
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[Service]
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Type=simple
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User=root
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Group=root
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WorkingDirectory=/opt/zenai-kpc-python
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EnvironmentFile=/opt/zenai-kpc-python/.env
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Environment=PYTHONNOUSERSITE=1
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Environment=PATH=/opt/zenai-kpc-python/venv/bin:/usr/local/bin:/usr/bin:/bin
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ExecStart=/opt/zenai-kpc-python/venv/bin/python counter_live_rknn.py
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TimeoutStopSec=30
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KillSignal=SIGTERM
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Restart=always
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RestartSec=10
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StartLimitInterval=120s
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StartLimitBurst=5
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NoNewPrivileges=true
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ProtectHome=true
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PrivateTmp=false
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[Install]
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WantedBy=multi-user.target
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[Unit]
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Description=ZenAI KPC Dashboard (Flask)
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Documentation=file:///opt/zenai-kpc-python/DEPLOY.md
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After=network-online.target zenai-kpc-counter.service
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Wants=network-online.target
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[Service]
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Type=simple
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User=root
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Group=root
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WorkingDirectory=/opt/zenai-kpc-python
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EnvironmentFile=/opt/zenai-kpc-python/.env
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Environment=PATH=/opt/zenai-kpc-python/venv/bin:/usr/local/bin:/usr/bin:/bin
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Environment=FLASK_DEBUG=false
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ExecStart=/opt/zenai-kpc-python/venv/bin/python counter_dashboard.py
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TimeoutStopSec=15
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KillSignal=SIGTERM
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Restart=always
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RestartSec=5
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StartLimitInterval=60s
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StartLimitBurst=3
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NoNewPrivileges=true
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ProtectHome=true
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PrivateTmp=false
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[Install]
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WantedBy=multi-user.target
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Reference in new issue
Block a user