# QAic QDetect layers

The QDetect layer is a proposed layer provided using Python to import
and replace the existing detection layers (YoloLayer, SSDLayer, and so
on) in the object detection models. This pluggable layer will eliminate
the quantization-sensitive operations and will implement a custom
operator that’s supported in the AIC backend.

QDetect layers can be applied on a pregenerated ONNX model or can be
included in the PyTorch source code itself and registered as a custom
op.

- [Model preparation](https://docs.qualcomm.com/doc/80-99100-3/topic/qaic_qdetect_layers_model_preparation.html)
- [Compilation using `qaic-compile`](https://docs.qualcomm.com/doc/80-99100-3/topic/compilation_using_qaic_compile.html)

Last Published: Aug 25, 2026

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