Advanced Settings

1. Run benchmarking on CPU/NPU/GPU.

By default, the configuration is set to use the CPU. If you want to benchmark the application on GPU or NPU, please update the device value in workload_to_pipeline.json.

make  benchmark

2. See the benchmarking results.

make  consolidate-metrics

cat benchmark/metrics.csv

3.🛠️ Other Useful Make Commands.

• make validate-all-configs — Validate all configuration files
• make clean-images — Remove dangling Docker images
• make clean-containers — Remove stopped containers
• make clean-all — Remove all unused Docker resources

4.⚙️ Configuration

The application is highly configurable via JSON files in the configs/ directory:

• camera_to_workload.json: Maps each camera to one or more workloads. To add or remove a camera, edit the lane_config.cameras array in this file. Each camera entry can specify its video source, region of interest, and assigned workloads.
  • Example:

    {
      "lane_config": {
        "cameras": [
          {
            "camera_id": "cam1",
            "fileSrc": "sample-media/video1.mp4",              
            "workloads": ["items_in_basket", "multi_product_identification"],
            "region_of_interest": {"x": 100, "y": 100, "x2": 800, "y2": 600}
          },
          ...
        ]
      }
    }
    

• workload_to_pipeline.json: Maps each workload name to a pipeline definition (sequence of GStreamer elements and models). To add or update a workload, edit the workload_pipeline_map in this file.
  • Example:

    {
      "workload_pipeline_map": {
        "items_in_basket": [
          {"type": "gvadetect", "model": "yolo11n", "precision": "INT8", "device": "CPU"},
          {"type": "gvaclassify", "model": "efficientnet-v2-b0", "precision": "INT8", "device": "CPU"}
        ],
        ...
      }
    }
    

To try a new camera or workload: 1. Edit configs/camera_to_workload.json to add your camera and assign workloads. 2. Edit configs/workload_to_pipeline.json to define or update the pipeline for your workload. 3. (Optional) Place your video files in the appropriate directory and update the fileSrc path. 4. Re-run the pipeline as described above.

📁 Project Structure

• configs/ — Configuration files (camera/workload mapping, pipeline mapping)
• docker/ — Dockerfiles for downloader and pipeline containers
• docs/ — Documentation (HLD, LLD, system design)
• download-scripts/ — Scripts for downloading models and videos
• src/ — Main source code and pipeline runner scripts
• Makefile — Build automation and workflow commands

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