andrew/karung-counting-feedmill-semarang

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docs: add CHANGELOG.md, sync all guides with config.yaml migration

- CHANGELOG.md (Keep-a-Changelog, dated entries from git history)
- README: production pipeline framing, config table, layout, flags, changelog link
- configuration.md: legacy env overrides, zones geometry-only, archive paths
- scripts.md: current flags, correct archive/ paths, tracked vs ignored weights
- deployment.md: config.yaml in sync list, model_mode location, /api/model-modes
- models.md + architecture.md: config.yaml pointers, deprecated src/config.py

2026-09-17 12:04:56 +07:00

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Deployment (Jetson)

Repo: https://git.proit.id/andrew/karung-counting-feedmill-semarang (git remote set-url origin <url> after the ervan → andrew transfer).

Systemd services

Unit	Runs	After
`karung-counter.service`	`/usr/bin/python3 predict.py` (cwd `/home/jetson/karung`, `QT_QPA_PLATFORM=offscreen`)	`network.target`
`karung-counter-dashboard.service`	`/usr/bin/python3 counter_dashboard.py`	`network.target` + counter
`mediamtx.service`	MediaMTX restream (see `zones.json:external_stream_url`)	—

Both app units: Restart=always, RestartSec=5, load EnvironmentFile=/home/jetson/karung/.env.

sudo systemctl enable --now karung-counter karung-counter-dashboard
sudo systemctl restart karung-counter karung-counter-dashboard
systemctl status karung-counter karung-counter-dashboard --no-pager

Deploy flow (`deploy_to_jetson.py`)

Paramiko sync of templates/{operator,monitoring,base}.html, counter_dashboard.py, predict.py, config.yaml, .env plus models/*.engine (v4-best, yolo11n-sack+box, best, truck-detector, model_karung_truk) → 192.168.192.96:/home/jetson/karung/ (creates remote models/ if missing, skips missing local files), then restarts both services and checks status + ports (5000/5721). Run from the dev machine. .pt/.onnx stay local-only (dev/export).

TensorRT export

On the Jetson (needs CUDA): python3 export_model.py models/<name>.pt exports to FP16 .engine next to the .pt (default: karung-dimuat seg model). Production loads .engine only — see models/modelREADME.md for which weights each mode uses.

Runtime data files

SQLite jetson_counter.db: batches(counting_date, batch_number, camera_name, object_label, count, start/end_time), daily_summaries(...).
current_batch.json (crash recovery), batch_mode.json (manual/auto batch mode only — the model mode lives in config.yaml), batch_history_folder/batch_<ts>.json + hasil_perhitungan.json (per-batch reports).
Live frame: /dev/shm/jetson-counter/live_frame.jpg (written every 2nd frame, consumed by /api/live-video MJPEG).
Helpers: check_jetson_db.py (root); retired ops scripts in archive/ (backup.py, dump_db.py, migrate_jetson_db.py, merge_batches_*.py, update_batches.py, diagnose_truck_jetson.py).

Dashboard (`counter_dashboard.py`)

Pages: / + /monitoring, /operator (manual start/stop, mode switch), /history, /analytics. Key APIs: /api/live-video, /api/current-batch, /api/previous-batch, /api/batch/{start,stop,mode}, /api/model-modes (mode list is derived from config.yaml, so future modes appear automatically), /api/summary, /api/daily-data, /api/day-detail/<date>, /api/recent-batches, /api/available-dates, /api/export-daily-csv, /api/export-day-csv/<date> (CSV + Excel via openpyxl).

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