Getting Started
Step by step instructions:
-
Download the models using download_models/downloadModels.sh
make download-models
-
Update github submodules
make update-submodules
-
Download sample videos used by the performance tools
make download-sample-videos
-
Run the LP application
make run-render-mode
NOTE:- User can directly run single make command that internally called all above command and run the Loss Prevention application.
-
Run Loss Prevention appliaction with single command.
6. View the Dynamically Generated GStreamer Pipeline.make run-lp
Since the GStreamer pipeline is generated dynamically based on the provided configuration(camera_to_workload and workload_to_pipeline json), the pipeline.sh file gets updated every time the user runs make run-lp or make benchmark. This ensures that the pipeline reflects the latest changes.
src/pipelines/pipeline.sh
-
Verify Docker containers
Result:docker ps --all
NAMES STATUS IMAGE src-pipeline-runner-1 Up 17 seconds (healthy) pipeline-runner:lp model-downloader Exited(0) 17 seconds model-downloader:lp
-
Verify Results
After starting Automated Self Checkout you will begin to see result files being written into the results/ directory. Here are example outputs from the 3 log files.
gst-launch_
pipeline
r
-
Stop the demo using docker compose down
make down-lp