Delete runtime/config.example.yml

runtime/config.example.yml

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-# =============================================================================
-# MBFS Sentinel - Configuration Template
-# =============================================================================
-#
-# Usage:
-#   1. Copy this file to config.yml:    cp config.example.yml config.yml
-#   2. Update values to match your environment
-#   3. Restart mbfs-sentinel to apply changes
-#
-# Notes:
-#   - All paths can be relative (to the executable) or absolute
-#   - Durations use seconds unless noted otherwise
-#   - Set 'enabled: true' on any plugin you want to activate
-#
-# =============================================================================
-
-
-# =============================================================================
-# General Settings
-# =============================================================================
-general:
-  project_name: MBFS Sentinel       # Display name shown in UI and logs
-  port: 8003                        # HTTP API port (Axum server)
-  dev_mode: false                   # Enable development mode (extra logging, relaxed checks)
-  device_id: c9869e48ab4a2341fe4e08587b20d6c402da59ce2e26d934b9d3d6d503e0bd5a  # Unique device identifier (from mbfs-mv-core)
-
-# =============================================================================
-# Database (PostgreSQL + pgvector)
-# =============================================================================
-database:
-  # PostgreSQL connection URL
-  # Format: postgresql://user:password@host:port/database?sslmode=disable
-  url: "postgresql://root:123123@localhost:5434/dev?sslmode=disable"
-
-  # Secret key for signing JWT tokens (MUST change in production!)
-  secret_key: "secret"
-
-# =============================================================================
-# MinIO Storage (S3-compatible object storage)
-# =============================================================================
-# Used for storing face crops, event snapshots, evidence images/videos.
-# Any S3-compatible service can be used (AWS S3, MinIO, etc.)
-# =============================================================================
-minio:
-  endpoint: "localhost:9000"        # MinIO server host:port
-  access_key: "minioadmin"          # Access key (username)
-  secret_key: "minioadmin"          # Secret key (password)
-  bucket: "mbfs-sentinel"           # Bucket name for all stored objects
-  secure: false                     # Use TLS/SSL connection (true for HTTPS)
-  url: http://localhost:9000        # Public-facing URL for generating download links
-
-# =============================================================================
-# AI Models
-# =============================================================================
-# Directory and filenames for core ONNX models (face detection & recognition).
-# Plugin-specific models are configured in their respective sections below.
-# =============================================================================
-models:
-  dir: './models'                              # Path to model files directory
-  detection_name: ""    # Face detection model (RetinaFace)
-  recognition_name: ""  # Face recognition/embedding model (ArcFace)
-
-# =============================================================================
-# Batch Processing
-# =============================================================================
-# Controls how frames are batched before inference to maximize GPU throughput.
-# Larger batches = higher throughput but more latency and VRAM usage.
-# =============================================================================
-batch:
-  detection_size: 24              # Face detection batch size (frames per batch)
-  recognition_size: 96            # Face recognition batch size (face crops per batch)
-  collection_timeout_ms: 100      # Max wait time to fill a batch before processing (ms)
-
-# =============================================================================
-# Worker Threads
-# =============================================================================
-workers:
-  num_ai: 3                       # Number of AI inference worker threads
-  upload: 24                      # Number of upload worker threads (MinIO/S3)
-
-# =============================================================================
-# Face Tracking
-# =============================================================================
-# Settings for tracking detected faces across consecutive frames.
-# Used by face recognition to maintain identity continuity.
-# =============================================================================
-tracking:
-  high_confidence_threshold: 0.65 # Min confidence for a high-quality face match
-  timeout: 2.0                    # Seconds before a tracked face expires (no re-detection)
-  similarity: 0.55                # Cosine similarity threshold for re-identification
-  log_cooldown: 3.0               # Min seconds between logging the same face identity
-  min_detections: 2               # Min detection count before a face is logged as event
-
-# =============================================================================
-# Image Upload
-# =============================================================================
-upload:
-  queue_max_size: 100             # Max pending uploads in queue (overflow is dropped)
-  jpeg_quality: 70                # JPEG compression quality for uploaded images (0-100)
-
-# =============================================================================
-# Camera Manager
-# =============================================================================
-# Connection to the external camera management service.
-# Sentinel periodically sends a survival signal to indicate it is alive.
-# =============================================================================
-camera_manager:
-  url: http://localhost:8000                # Camera manager API base URL
-  survival_signal_interval: 10              # Interval in seconds for survival heartbeat
-
-# =============================================================================
-# Core AI Node (Cluster mode)
-# =============================================================================
-# URL of the central AI node when running in distributed/cluster mode.
-# =============================================================================
-core_ai:
-  url: http://10.8.0.3:8003
-
-# =============================================================================
-# TensorRT Configuration
-# =============================================================================
-# TensorRT engine caching speeds up model loading after first run.
-# Engine files are GPU-specific and will be rebuilt if hardware changes.
-# =============================================================================
-tensorrt:
-  enabled: true                   # false = skip TensorRT, use CUDA (faster startup, slower inference)
-  cache_dir: trt_cache            # Directory for cached TensorRT engine files
-  lib_dir: null                   # Custom TensorRT library path (null = system default)
-
-# =============================================================================
-# License
-# =============================================================================
-license:
-  key: ''                         # License key (obtained from license server)
-  active_key: ''                  # Active license key (set after successful activation)
-
-license_server:
-  url: https://ai-mv-core.mbfs.com.vn      # License server URL
-  check_interval_secs: 86400                # License recheck interval (86400 = 24 hours)
-
-# =============================================================================
-# Processing Loop
-# =============================================================================
-# Low-level tuning for the frame processing pipeline.
-# Default values work well for most setups. Only adjust if needed.
-# =============================================================================
-processing:
-  max_batch_size: 24              # Max frames per processing batch
-  loop_sleep_ms: 10               # Sleep between processing loops (ms)
-  channel_buffer_size: 256        # Channel buffer for frame pipeline
-  face_log_queue_size: 256        # Face event logging queue size
-  face_log_workers: 2             # Face event logging worker threads
-  dispatch_max_fps: 15            # Default max dispatch rate per pipeline runner (fps).
-                                  # Coordinator drops batches dispatched faster than this
-                                  # to avoid wasting Arc clones + mutex contention on frames
-                                  # the runner can't keep up with. Camera decode rate is
-                                  # capped separately at 15fps in mbfs-camera.
-                                  # Plugins can override per-plugin via manifest.toml:
-                                  #   [runtime]
-                                  #   max_fps = 8
-
-
-# =============================================================================
-# Plugins - AI Pipeline Configurations
-# =============================================================================
-#
-# Each plugin can be independently enabled/disabled. Common sub-sections:
-#
-#   enabled        - Whether the plugin is active (true/false)
-#   confidence     - Min detection confidence threshold (0.0 - 1.0)
-#   nms_threshold  - Non-Maximum Suppression IoU threshold (0.0 - 1.0)
-#
-#   tracking:      - ByteTrack multi-object tracker settings
-#     enabled                - Enable/disable object tracking
-#     high_conf_threshold    - High confidence detection threshold
-#     low_conf_threshold     - Low confidence detection threshold
-#     confirm_frames         - Frames needed to confirm a new track
-#     max_lost_frames        - Max frames before a lost track is removed
-#
-#   alert:         - Alert system settings (consecutive detection triggers)
-#     consecutive_threshold  - Consecutive detections needed to trigger alert
-#     max_miss               - Max missed frames before resetting alert counter
-#     cooldown_secs          - Cooldown between alerts for the same object
-#
-#   data_lake:     - Event storage configuration
-#     enabled          - Enable event logging
-#     bucket_prefix    - MinIO bucket prefix for this plugin's events
-#     min_count        - Min detection count before saving event
-#     jpeg_quality     - JPEG quality for event snapshots (0-100)
-#     queue_size       - Event processing queue size
-#     workers          - Number of event processing workers
-#     batch_size       - Events per batch write
-#     parquet_enabled  - Enable Parquet file export
-#     parquet_batch_size - Rows per Parquet batch
-#     save_json        - Save raw JSON alongside Parquet
-#     db_enabled       - Write events to PostgreSQL
-#     db_batch_size    - DB insert batch size
-#     db_batch_timeout_ms - Max wait before flushing DB batch (ms)
-#     db_channel_size  - DB write channel buffer size
-#     save_crops       - Save cropped detection images to MinIO
-#     crop_jpeg_quality - JPEG quality for crop images (0-100)
-#
-#   dedup:         - Deduplication settings (prevent duplicate events)
-#     cooldown_seconds             - Min seconds between events for same object
-#     grid_size                    - Spatial grid cell size for position-based dedup
-#     high_confidence_threshold    - Confidence above which dedup is stricter
-#     significant_count_threshold  - Detection count to consider object significant
-#     max_tracked_per_camera       - Max tracked objects per camera for dedup
-#
-# =============================================================================
-plugins:
-
-  # ---------------------------------------------------------------------------
-  # Shared Models
-  # ---------------------------------------------------------------------------
-  # Model files referenced by multiple plugins. Avoids duplicating filenames.
-  # These are loaded once and shared across plugins that need them.
-  # ---------------------------------------------------------------------------
-  shared_models:
-    detection_model: det_10g_fp16_dynamic.onnx.enc      # Face detection (RetinaFace)
-    recognition_model: mbfs_rec_vit_b_v3.onnx.enc       # Face recognition (ViT)
-    human_detection_model: mbfs_human_det_v4.onnx       # Human/person detection (YOLO)
-    helmet_model: helmet_dt_v10.onnx                    # Helmet detection
-    lpr_detection_model: lp_detection_v4.onnx           # License plate detection
-    lpr_ocr_model: mbfs_ocr_license_plate_b16_v5.onnx  # License plate OCR
-    vehicle_model: yolov8_coco.onnx                     # Vehicle detection (COCO classes)
-
-  # ---------------------------------------------------------------------------
-  # Face Recognition (builtin)
-  # ---------------------------------------------------------------------------
-  # Detects faces, extracts embeddings, and matches against enrolled identities.
-  # Requires: detection_model + recognition_model from shared_models.
-  # ---------------------------------------------------------------------------
-  face_recognition:
-    enabled: false
-    min_detection_score: 0.7              # Min face detection confidence
-    min_size: 32                          # Min face size in pixels (width or height)
-    min_ratio: 0.0001                     # Min face area ratio relative to frame
-    unknown_min_score: 0.50               # Min score to classify as "unknown" (below = discard)
-    enrollment_min_detection_score: 0.7   # Stricter detection threshold for face enrollment
-    enrollment_min_size: 100              # Min face size for enrollment (px)
-    enrollment_max_angle: 15.0            # Max yaw/pitch angle for enrollment (degrees)
-    data_lake:
-      enabled: true
-      bucket_prefix: face-recognition-events
-      min_count: 1
-      jpeg_quality: 85
-      queue_size: 512
-      workers: 1
-      batch_size: 16
-      parquet_enabled: true
-      parquet_batch_size: 1000
-      save_json: false
-      db_enabled: true
-      db_batch_size: 32
-      db_batch_timeout_ms: 100
-      db_channel_size: 512
-      save_crops: true
-      crop_jpeg_quality: 90
-    dedup:
-      cooldown_seconds: 5.0
-      grid_size: 100.0
-      high_confidence_threshold: 0.65
-      significant_count_threshold: 3
-      max_tracked_per_camera: 50
-
-  # ===========================================================================
-  # Dynamic Plugins
-  # ===========================================================================
-  # Plugins loaded at runtime from DLLs in the plugins/ directory.
-  # Each plugin has a manifest.toml defining its models and capabilities.
-  # Config values here override manifest defaults.
-  # ===========================================================================
-  dynamic_plugins:
-
-    # -------------------------------------------------------------------------
-    # Human Detection
-    # -------------------------------------------------------------------------
-    # Detects humans/persons in the frame. Foundation for many other plugins.
-    # Model: human_detection_model from shared_models.
-    # -------------------------------------------------------------------------
-    human_detection:
-      enabled: false
-      confidence: 0.75
-      nms_threshold: 0.45
-      alert:
-        consecutive_threshold: 5
-        max_miss: 2
-        cooldown_secs: 10.0
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 3
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: human-detection-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 3.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # Facial Expression Recognition
-    # -------------------------------------------------------------------------
-    # Classifies facial expressions (happy, sad, angry, surprised, etc.).
-    # Two-stage: face detection -> expression classification.
-    # -------------------------------------------------------------------------
-    facial_expression:
-      enabled: false
-      confidence: 0.5
-      nms_threshold: 0.45
-      alert:
-        consecutive_threshold: 5
-        max_miss: 2
-        cooldown_secs: 10.0
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 3
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: facial-expression-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 3.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # Object Detection (General)
-    # -------------------------------------------------------------------------
-    # General-purpose object detection using COCO or custom classes.
-    # Useful for counting/tracking arbitrary object types.
-    # -------------------------------------------------------------------------
-    object_detection:
-      enabled: false
-      confidence: 0.75
-      nms_threshold: 0.45
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 3
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: object-detection-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 3.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # Smoke & Fire Detection
-    # -------------------------------------------------------------------------
-    # Detects smoke and fire in the frame. Triggers alerts when detected
-    # consecutively to reduce false positives.
-    # -------------------------------------------------------------------------
-    smoke_fire_detection:
-      enabled: false
-      confidence: 0.75
-      alert:
-        consecutive_threshold: 5          # Consecutive detections to trigger alert
-        max_miss: 2                       # Max missed frames before reset
-        cooldown_secs: 10.0               # Alert cooldown (seconds)
-      data_lake:
-        enabled: true
-        bucket_prefix: smoke-fire-detection-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 3.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # Behavior Detection
-    # -------------------------------------------------------------------------
-    # Detects abnormal behaviors (loitering, falling, running, etc.).
-    # Uses human detection + tracking to analyze movement patterns.
-    # -------------------------------------------------------------------------
-    behavior_detection:
-      enabled: false
-      confidence: 0.75
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 5                 # Higher confirm frames for behavior analysis
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: behavior-detection-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 3.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # Helmet Detection
-    # -------------------------------------------------------------------------
-    # Detects whether people are wearing safety helmets (construction sites, etc.).
-    # Triggers alerts for "no helmet" detections.
-    # -------------------------------------------------------------------------
-    helmet_detection:
-      enabled: false
-      confidence: 0.75
-      alert:
-        consecutive_threshold: 5
-        max_miss: 2
-        cooldown_secs: 10.0
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 3
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: helmet-detection-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 3.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # Weapon Detection
-    # -------------------------------------------------------------------------
-    # Detects weapons (guns, knives, etc.) in the frame.
-    # Lower confidence threshold and shorter cooldown for safety-critical alerts.
-    # -------------------------------------------------------------------------
-    weapon_detection:
-      enabled: false
-      confidence: 0.5                     # Lower threshold for safety-critical detection
-      nms_threshold: 0.45
-      alert:
-        consecutive_threshold: 5
-        max_miss: 2
-        cooldown_secs: 5.0                # Shorter cooldown for urgent alerts
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 3
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: weapon-detection-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 5.0             # Longer dedup for weapon events
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # Phone Usage Detection
-    # -------------------------------------------------------------------------
-    # Two-stage: detect humans -> crop -> classify phone usage.
-    # Higher confidence threshold to reduce false positives on small objects.
-    # -------------------------------------------------------------------------
-    phone_usage_detection:
-      enabled: false
-      confidence: 0.8                     # Higher threshold (small object, prone to FP)
-      nms_threshold: 0.45
-      crop_padding: 0.1                   # Extra padding around human crop for context
-      alert:
-        consecutive_threshold: 5
-        max_miss: 2
-        cooldown_secs: 5.0
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 3
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: phone-usage-detection-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 30.0            # Longer cooldown to avoid spam
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # Fight Detection
-    # -------------------------------------------------------------------------
-    # Detects physical fights/altercations between people.
-    # Uses pose or interaction analysis on tracked humans.
-    # -------------------------------------------------------------------------
-    fight_detection:
-      enabled: false
-      confidence: 0.5
-      nms_threshold: 0.45
-      alert:
-        consecutive_threshold: 5
-        max_miss: 2
-        cooldown_secs: 5.0
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 3
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: fight-detection-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 3.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # People Counting (migrated from builtin to dynamic plugin)
-    # -------------------------------------------------------------------------
-    people_counting:
-      enabled: false
-      confidence: 0.25
-      nms_threshold: 0.45
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 3
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: people-counting-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 3.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # License Plate Recognition (migrated from builtin to dynamic plugin)
-    # -------------------------------------------------------------------------
-    license_plate_recognition:
-      enabled: false
-      confidence: 0.5
-      nms_threshold: 0.45
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 2
-        max_lost_frames: 15
-      data_lake:
-        enabled: true
-        bucket_prefix: license-plate-recognition-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 10.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-    # -------------------------------------------------------------------------
-    # Traffic Violation Detection (migrated from builtin to dynamic plugin)
-    # -------------------------------------------------------------------------
-    traffic_violation_detection:
-      enabled: false
-      confidence: 0.5
-      nms_threshold: 0.45
-      tracking:
-        enabled: true
-        high_conf_threshold: 0.5
-        low_conf_threshold: 0.1
-        confirm_frames: 3
-        max_lost_frames: 30
-      data_lake:
-        enabled: true
-        bucket_prefix: traffic-violation-events
-        min_count: 1
-        jpeg_quality: 85
-        queue_size: 512
-        workers: 2
-        batch_size: 16
-        parquet_enabled: true
-        parquet_batch_size: 1000
-        save_json: false
-        db_enabled: true
-        db_batch_size: 16
-        db_batch_timeout_ms: 100
-        db_channel_size: 256
-        save_crops: true
-        crop_jpeg_quality: 90
-      dedup:
-        cooldown_seconds: 3.0
-        grid_size: 100.0
-        high_confidence_threshold: 0.75
-        significant_count_threshold: 5
-        max_tracked_per_camera: 50
-
-# =============================================================================
-# Logging
-# =============================================================================
-logging:
-  enabled: true
-  dir: logs                       # Log files directory (relative to executable)
-  max_days: 7                     # Auto-cleanup logs older than N days