.. _ai-yolox-detection-example:

Object detection
================

Load YOLOX into the AI inference handler, run detection on a few camera frames, and print per-frame fetch / detect timings.

.. note::
   ``load_model`` creates an ONNX Runtime session on the appliance and keeps it
   resident until you call :meth:`~olo.ai.Model.unload` (or exit a ``with`` /
   ``try``/``finally`` that unloads). Expect a noticeable load delay, and the
   first :meth:`~olo.ai.yolo.YoloDetector.detect` call is often slower than
   later ones (session and accelerator warmup). Reuse one loaded session across frames rather than loading per image.

.. tab-set::
    :sync-group: sdk-language

    .. tab-item:: Python
        :sync: python

        .. literalinclude:: scripts/ai-yolox-detection.py
           :language: python

    .. tab-item:: TypeScript
        :sync: typescript

        .. literalinclude:: scripts/ai-yolox-detection.ts
           :language: typescript