Export targets¶
| Target | Edition | What you get | Runs on |
|---|---|---|---|
| ONNX Runtime (CPU) | Standard | One self-describing .onnx; optional .zip with classes.txt, metadata.json, README |
ctrlX CORE or IPC CPU |
| Hailo accelerator | Pro | Bundle for the Hailo Dataflow Compiler: INT8 calibration set from your images, model script, decode data (metadata.json, dgqp.npz). Tools ▸ Compile Hailo Bundle to .hef… produces the .hef |
ctrlX CORE X7 with Hailo-8 or Hailo-8L |
| NVIDIA GPU (CUDA / TensorRT) | Pro | Graph ready for trtexec (no NMS, batch 1), plus run_nvidia.py as a worked example |
ctrlX IPC with NVIDIA GPU |
- Hailo is proven end to end on a ctrlX CORE X7 with Hailo-8. Since 1.7.1, parcel models with package corners also run on Hailo.
- NVIDIA on the ctrlX IPC: on-device demonstration in progress.
Measured result
On a ctrlX CORE X7, a Model Bench parcel model runs in 13.05 ms per frame on the Hailo-8 accelerator, against 246 ms on the X7's CPU — 19 times faster.
Screenshots to come
- S12 — Export ONNX dialog with the Target list open.
- S20 — Compile Hailo Bundle: preflight checks or compile in progress.
- S21 — Visual Detector web UI on the ctrlX device with live detections from a Model Bench model.