karung-counting-feedmill-semarang/CHANGELOG.md

Changelog

All notable changes to this project are documented here. Format follows Keep a Changelog (dated entries; no version tags are cut in this repo — POC stage, main is the release line).

[Unreleased]

Added

• DO-gated manual batch mode (auto default · do_manual · legacy manual): smartphone photo capture → OCR draft → plate-grouped start gates → net expected/counted on live panel → stop soft-warn + force → discard only when both gross count and box_loading are 0.
• config.yaml batch.default_mode + do: block; DoConfig in src/config_loader.py; runtime $OUTPUT_DIR/do_settings.json.
• delivery_orders table + additive batches columns (plate, do_numbers, expected_*, net_*); photo tree do_photos/YYYY-MM-DD/ (7-day retention).
• APIs: POST /api/batch/stop-preview, DO CRUD + POST /api/do/upload, GET|POST /api/do/settings (all gated fields office-only: require_plate/require_do/ocr_engine, 403 on operator), office-only mode/model_mode POST (403 on operator; 409 when batch active).
• src/do_batch.py (pure gates/nets/units), src/do_ocr.py (extract_do_fields rapid|tesseract|paddle|none).
• RapidOCR default engine (rapidocr_onnxruntime, bundled PP-OCR models); tesseract + paddle kept as backups, explicit error if a dep is missing.
• Operator DO panel (no OCR toggle); monitoring 3-way mode switch + model mode + OCR selector with labels RapidOCR (Default, Light & Accurate) / Tesseract (Backup, Light) / PaddleOCR (Accuracy, Heavy to run) / None (Manual) + require-plate controls; history/export plate, DO, expected, net columns.
• ERD.md (Mermaid ERD, repo root; superseded docs/do-erd.md); tests tests/test_do_batch.py.
• History Klip button → office-only GET /api/batch-clip/<date>/<batch_number> trims+concatenates motionEye recordings to the batch window (src/clip.py), download b<n>-<date>-<HH-MM-SS>.mp4.

Changed

• OCR engine default rapid (was tesseract) across config.yaml, DoConfig, empty_do_settings, extract_do_fields; ocr_engine write moved office-only (was both ports); OCR engine selector removed from operator page.
• Default batch mode seed auto (was hard-coded manual when batch_mode.json missing); predict.py accepts do_manual as operator-driven and persists sack unloading for net-at-stop.
• Finalize discard rule (dashboard stop and predict.py finalize_batch): keep row if either net ≠ 0 (box-only batches no longer dropped).
• Batch discard rule now gross-based: drop only when count == 0 and box_loading == 0 (was both nets 0 — kept rows like count=0, unloading=7).
• Event log wording: masuk/keluar now match event direction (unloading no longer logged as masuk, TOTAL line follows direction); wired the existing-but-unused src/logger.py CSVLogger into predict.py (batch_summary.csv, sack_events.csv under output.dir).

2026-09-18 — Config tuning: Sack confidence and batch timeout

Changed

• config.yaml: Decreased models.detection_params.sack.conf from 0.35 to 0.30 for improved sack sensitivity.
• config.yaml: Decreased batch.timeout_seconds from 30.0 to 20.0 for faster batch cycle completion.
• config.yaml: Clarified deprecation note on batch.merge_threshold_seconds.

2026-09-17 — Unified config.yaml with extensible model presets

Added

• config.yaml — single canonical config (stream, models, counting knobs, batch, output paths, camera). Secrets/deployment-only values stay in .env.
• src/config_loader.py — stdlib-dataclasses + pyyaml loader, zero new dependencies. Missing file falls back to .env + legacy defaults with a UserWarning; MODEL_MODE env still honoured once with a DeprecationWarning.
• tests/test_config_loader.py — 8 smoke tests (load/validate, precedence, atomic mode-switch round-trip, YAML-only mode-E extension, legacy warnings).
• Per-class iou and min_bbox_area in models.detection_params (shared across modes; iou default 0.7 = Ultralytics default, no behaviour change).
• --config CLI flag on predict.py (default: config.yaml next to predict.py).

Changed

• Model modes are data: config.yaml → models.modes holds engines (path key + contributed classes) and class filters only. predict.py derives tracker roles structurally — adding mode E/F/... needs no code change, and the dashboard /api/model-modes lists new modes automatically.
• Dashboard POST /api/batch/mode {"model_mode": "X"} validates against config.yaml and persists atomically (tmp+replace, comments preserved) to models.active_mode. Manual karung-counter restart still required.
• batch_mode.json keeps only the manual/auto batch mode; its legacy model_mode key is ignored (warned when it disagrees).
• zones.json keeps geometry only (polygons + left/right limits); legacy knob keys there are ignored with a warning — config.yaml counting.* is canonical.
• deploy_to_jetson.py also syncs config.yaml.
• src/tracking.py / src/detection.py accept an iou parameter (default 0.7, v3 callers unaffected).

2026-09-15 — Default model mode B → C

• Production default is now Mode C (combined v4 sack+truck + yolo11n box-only on a dedicated tracker) instead of Mode B (shared sack+box tracker). Changed in predict.py, counter_dashboard.py, .env.example, and docs. Sack path uses the proven v4 model; sack/box track-ID spaces no longer collide.

2026-09-14 — models/modelREADME.md rename

• models/README.md → models/modelREADME.md to avoid confusion with the root README. No content change.

2026-09-11 — Model weights tracked, per-mode matrix

• models/*.pt + *.onnx are now git-tracked (clone-ready); *.engine stays gitignored (rebuildable via export_model.py on the Jetson).
• All weights moved under models/ with a per-mode detector/filter matrix (models/modelREADME.md); predict.py paths, deploy_to_jetson.py, and docs updated.
• Multi-model modes (A/B/C/D, default B at the time) + box counting + manual-mode banner (6e4af50).

2026-09-10 — Single predict.py entrypoint, experiments archived

• Production + dev CLI unified in predict.py (runs as karung-counter.service with zero args). Retired experiments moved to archive/ via git mv (predict_new.py, rpo_iki/, simple_predict.py, check/merge/test scripts).
• Docs guides added (docs/architecture.md, models.md, configuration.md, scripts.md) plus DB/batch helper scripts; pytest smoke tests + CI.

2026-08-24 — Manual & auto batch modes, dual-port dashboards

• Manual/auto batch counting, operator (port 5000) + monitoring (port 5721) dashboards, historical batch data views and corrections.