Skip to navigation

Version 3.3.0

Features

  • Deployment profiles:

    • Added Warehouse Helm charts for 2D, 3D, and MV3DT profiles, with optional agents in the 2D chart.
    • Added support for RTX PRO 4500 Blackwell and GB300 hardware profiles.
  • Launchable and Skills:

    • Added Warehouse deployment support to the Build Vision AI skill, covering 2D, 3D, MV3DT, and Auto Calibration profiles, Kafka / Redis variants, and minimal / extended configurations.
    • Added the vss-deploy-warehouse-helm skill and a standalone compute_stream_cap.py helper to set stream limits based on GPU hardware.
    • Updated Behavior Analytics skills for the Build Vision Agent to deploy standalone and combined Search + Alerts workloads, with guidance for proximity alerts, FOV counting, ROI bounding-box overlap, object speed, and people counting.
    • Updated the Warehouse Brev launchable notebook for the refactored Docker Compose configuration and unified Auto Calibration profile.
  • Microservices:

    • Behavior Analytics:

      • Added behaviorEmitOnce to emit a final behavior when a track ends, with per-sensor event-time handling, behavior holdback, and shutdown flushing. Real-time emission remains the default, and isComplete identifies completed behaviors.
      • Added configurable ROI ENTRY / EXIT detection based on bounding-box overlap.
    • Auto Calibration: Added support for image-mode calibration

    • Video IO & Storage (VIOS): Added DASH live-stream playback as an alternative to WebRTC.

    • MV3DT: Integrated ReID embeddings with Kafka and Elasticsearch ingestion support.

  • Models - Core AI models for perception and analytics:

    • Sparse4D - 3D Warehouse Models v2.3 and v3.0 - Updated models for synthetic and real-world Warehouse datasets, respectively. DATASET_TYPE selects the matching model, anchor, labels, and TensorRT engine configuration.
    • Perception models are now downloaded from the NGC TAO registry during deployment instead of being bundled in the Warehouse app-data archive.

Improvements

  • Docker Compose:

    • Centralized NvStreamer, VSS Configurator, and Video Analytics API services and removed duplicated profile-specific configurations and Configurator initialization services.
    • Unified the Warehouse Auto Calibration profile to deploy NvStreamer, VIOS, Auto Calibration, and VSS Configurator together.
    • Reorganized .env and overrides.env configuration and updated Warehouse profile-selection defaults.
  • Microservices:

    • Behavior Analytics:

      • Combined Search and Alerts in a single Behavior Analytics main application script.
      • Refactored restricted-area and confined-area violation detection and ROI information handling, simplified trajectory and state management, tuned default pipeline worker counts, and improved worker-lifecycle and fatal-error reporting.
      • Enabled proximity, confined-area, and restricted-area incidents in the Warehouse 3D profile.
      • Updated ROI output to report restrictedAreaViolation=false when no objects are present.
    • Video Analytics API: Added readiness checks for Elasticsearch connectivity, the insertion-timestamp ingest pipeline, and required Kafka topics before starting the HTTP listener and accepting calibration uploads. Redis deployments ignore Kafka configuration.

    • Logstash:

      • Replicated Logstash ingestion pipelines and updated consumer groups per Kafka topic, with worker, batch, heap, and resource tuning to reduce Elasticsearch ingestion delays.
      • Added the Redis Stream input plugin source code, build documentation, and tests to the repository.
      • Improved Redis Stream plugin connection-pool lifecycle, graceful shutdown, duplicate-message handling, acknowledgment, and protobuf descriptor loading.
  • Models and hardware configuration:

    • Updated the maximum number of streams per GPU for RT-DETR and Sparse4D models.
    • Increased the RT-DETR Person-class detection limit from 20 to 50.
    • Added batch-size suffixes to TensorRT engine filenames to prevent incompatible engine reuse.
    • Tuned RTVI-VLM memory utilization and context length for RTX PRO 4500 Blackwell deployments.

Fixed Issues

  • Alerting and RTVI-VLM:

    • Fixed real-time alerts failing to initialize when Elasticsearch shards were not yet ready.
    • Fixed missing real-time VLM incidents caused by Redis message-field configuration.
    • Fixed RTVI-VLM inference failures caused by multimodal processor caching and request serialization.
  • Behavior Analytics: Fixed validation of violation-duration thresholds and expiration windows to accept fractional seconds.

  • SDRC: Fixed a startup race with RTVI-CV by waiting for perception readiness before adding streams.

  • Video IO & Storage (VIOS):

    • Fixed incorrect 3D bounding-box overlays caused by projecting boxes behind the camera.
    • Fixed missing overlays in downloaded recordings when Elasticsearch throttles metadata requests.

Version 3.2.1

Features

  • Models - Core AI models:

    • CR - Updated Cosmos3 Nano Reasoner (NIM) as the default VLM for Warehouse Blueprint.

Improvements

  • VSS Configurator: Fixed an issue with live RTSP stream configuration.

Version 3.2.0

Initial GitHub release of the VSS Warehouse Blueprint.

Features

  • New profiles introduced:

    • MV3DT profile.
    • Auto Calibration profile.
  • Launchable and Skills:

    • Warehouse deploy launchable notebook.
    • Warehouse deploy and debug skills.
    • Behavior Analytics standalone deploy skill.
    • Video Analytics API standalone deploy skill.
  • Microservices:

    • RTVI-VLM always-on alerts enabling Load Quality, PPE, Spillover, and Pathway / Unexpected Obstructions.

    • Replacement of local VLM with RTVI-VLM.

    • Auto Calibration:

      • Support for 3D profile deployment.
      • Support for image coordinates.
      • Support for RTSP as input.
    • Behavior Analytics: Added support for dynamic configuration changes.

    • Added dynamic configuration support in Video Analytics API to store and audit configuration changes of Behavior Analytics.

    • Spatial AI Data Utils:

      • Enable region and group assignment to global ROIs and tripwires.
      • Add evaluation tools for 3D IoU-based tracking evaluation.
      • Implement data validation and evaluation for 3D inference data.
      • Add visualization tools.
    • VSS Configurator:

      • Support toggling between Kafka and Redis configurations.
      • Support editing JSON configuration files.
    • SDR: Auto re-addition of streams on Docker restart for perception services.

Improvements

  • Docker Compose: Refactored to improve modularity of microservices.

  • Microservices:

    • Video Analytics API: Retry mechanism for Kafka broker, Elasticsearch, and related services.

    • Behavior Analytics: Retry mechanism for Kafka broker, Elasticsearch, Redis, MQTT, and related services.

    • Spatial AI Data Utils: Improved camera grouping algorithms.

    • VSS Configurator:

      • Added backup and cleanup support for calibration.json.
      • Ensured the calibration file schema is followed after VSS Configurator operations.
    • Alerting service:

      • VLM verification supports JSON output from VLM.
      • Improved VLM verification accuracy for Near Miss Violation by tuning prompts.
    • VIOS:

      • Added top-view image visualization support on Thor and Spark platforms.
      • Improved visualization of 3D bounding boxes by using individual camera timestamps when present.
  • Models - Core AI models for perception and analytics:

Version 3.1.0

Features

  • Introduced Minimal profile to deploy the minimal set of microservices to run on a machine with smaller resource footprint

Improvements

  • Microservices

    • Perception:
      • Perception microservice uses DeepStream SDK v9.0 to perform object detection and tracking.
      • Performance improvement for IGX Thor.
    • Behavior Analytics: Enhanced support for image coordinates based analytics.
    • Agents: Improved the multi-turn conversation capabilities.
  • Models - Core AI models for perception and analytics

Fixed Issues

  • Video IO & Storage (VIOS): Fixed issues with storage service.
  • VSS Configurator: Fixed issues with live RTSP stream configuration.

Version 3.0.0

Initial release of the VSS Warehouse Blueprint.

Features

  • Warehouse Blueprint Profiles - Layered architecture profiles combining microservices, blueprints, and AI agents for 2D and 3D applications

  • Microservices - Core components including video I/O and storage, behavior analytics, RESTful APIs, operations UI, AI agents and Auto Calibration.

    • Video IO & Storage (VIOS) – Microservice for ingesting camera streams (RTSP, WebRTC), managing video recording, playback, and persistent storage
    • Behavior Analytics – Real-time detection and analysis of warehouse events including object tracking, zone monitoring, and behavior pattern recognition
    • Video Analytics APIs – RESTful APIs providing programmatic access to analytics data, event streams, and video workflow management
    • Reference Video Analytics UI – Web-based dashboard for real-time monitoring, incident review, camera management, and analytics visualization
    • VSS Agent – Natural language interface powered by Nemotron Nano 9B v2 enabling conversational queries about incidents and automated report generation
  • Models - Core AI models for perception and analytics

Known Limitations

See Known Limitations for current constraints and workarounds.