How to Generate and Deploy Offline Package#

Overview#

The Offline Package Generator creates self-contained deployment packages for Metro Vision AI applications that can be deployed in environments without internet connectivity. This tool is specifically designed for environments with no internet connectivity where traditional cloud-dependent deployments are not feasible.

Prerequisites#

System Requirements#

  • Operating System: Linux (Ubuntu 20.04 or later)

  • Docker: Version 20.10.0 or higher

  • Docker Compose: Version 2.0.0 or higher

  • Storage Space: Minimum 15 GB available disk space

  • Memory: 8 GB RAM recommended

  • Internet Connection: Required for package generation only

Important: This process requires two environments - a connected system for package generation and an offline target system for deployment.

Step 1: Generate Offline Package#

Perform this step on a system with internet connectivity

Objective: Create a complete offline deployment package containing all necessary components for the Smart Parking application.

cd edge-ai-suites/metro-ai-suite/metro-vision-ai-app-recipe/smart-parking

./offline-package-generator.sh

What happens during generation:

  • Downloads and packages all Docker images (~2-3 GB)

  • Collects AI models and sample videos (~500 MB)

  • Gathers Grafana plugins and configurations (~100 MB)

  • Prepares deployment scripts and documentation

  • Creates a complete offline-package/ directory

Step 2: Prepare Package for Transfer#

Package the generated files for secure transport to offline environment

Objective: Create a compressed, transferable archive optimized for offline environments.

# Create a timestamped compressed package for easy identification
tar -czf smart-parking-offline-$(date +%Y%m%d-%H%M).tar.gz offline-package/

# Verify package integrity and size
ls -lh smart-parking-offline-*.tar.gz
tar -tzf smart-parking-offline-*.tar.gz | head -10

# Generate checksum for integrity verification
sha256sum smart-parking-offline-*.tar.gz > package-checksum.txt

Transfer the tar.gz package and checksum file to your offline environment:

Both files need to be transferred together for integrity verification

  • smart-parking-offline-YYYYMMDD-HHMM.tar.gz (main package)

  • package-checksum.txt (integrity verification file)

Transfer options for offline environments:

  • USB/External drive: Copy files to removable media

  • Secure network: Use SCP, SFTP, or approved file transfer protocols

  • Physical media: Burn to DVD/Blu-ray for highly secure environments

  • Satellite/RF links: For remote locations with limited connectivity

Step 3: Deploy in Offline Environment#

Execute deployment on the target system without internet connectivity

Objective: Deploy and start the Smart Parking application in a completely offline environment.

3.1 Extract and Prepare#

tar -xzf smart-parking-offline-*.tar.gz
sha256sum -c package-checksum.txt

cd offline-package/
ls -la

3.2 Load Docker Components#

chmod +x load-images.sh
./load-images.sh
docker images | grep -E "(grafana|influxdb|nginx|dlstreamer)"

3.3 Start the Application#

docker compose up -d
docker ps

Step 4: Run the Application#

4.1 Start Video Streams#

Start video streams to run video inference pipelines:

./sample_start.sh

4.2 Check Pipeline Status#

To check the status of the pipelines:

./sample_status.sh
Stop Pipelines

To stop the pipelines without waiting for video streams to finish replay:

NOTE: This will stop all the pipelines and the streams. DO NOT run this if you want to see smart parking detection.

./sample_stop.sh

4.3 View Application Output#

  1. Open a browser and navigate to https://127.0.0.1/grafana to access the Grafana dashboard.

    • Change 127.0.0.1 to your host IP if accessing remotely.

  2. Log in with the following credentials:

    • Username: admin

    • Password: admin

  3. Check under the Dashboards section for the application-specific preloaded dashboard.

  4. Expected Results: The dashboard displays real-time video streams with AI overlays and detection metrics.

Access Application Components#

Nginx Dashboard#

Grafana UI#

  • URL: https://127.0.0.1/grafana

  • Credentials:

    • Username: admin

    • Password: admin (You will be prompted to change it on first login)

  • The dashboard displays detected cars in the parking lot.

    Grafana Dashboard

NodeRED UI#

DL Streamer Pipeline Server#

Stop the Application#

To stop the application microservices, use the following command:

docker compose down