Order Accuracy

Overview

The Order Accuracy Pipeline System is an open-source reference implementation for building and deploying video analytics pipelines for retail order accuracy in Quick Servce Restaurant(QSR) use cases. It leverages Intel® hardware and software, GStreamer, and OpenVINO™ to enable scalable, real-time object detection and classification at the edge.

📋 Prerequisites

• Ubuntu 24.04 or newer (Linux recommended)
• Docker
• Make (sudo apt install make)
• Intel hardware (CPU, iGPU, dGPU, NPU)
• Intel drivers (see Intel GPU drivers)
• Sufficient disk space for models, videos, and results

🚀 QuickStart

The first run will download models, videos, and build Docker images. This may take some time.

1. Download models and videos, and run the Order Accuracy application.

make download-models
make update-submodules
make download-sample-videos
make run-render-mode

User can directly run single make command that internally called all above command and run the Order Accuracy application.

3. Run Order Accuracy appliaction with single command.

make run-demo

4. Stop all containers

make down

4. 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

5. See the benchmarking results.

make  consolidate-metrics

cat benchmark/metrics.csv

🛠️ Other Useful Make Commands.

• make clean-images — Remove dangling Docker images
• make clean-models — Remove all the downloaded models from the system
• make clean-all — Remove all unused Docker resources

📁 Project Structure

• configs/ — Configuration files (txt file with sample video URLs for inference)
• docker/ — Dockerfiles for downloader and pipeline containers
• 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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