ti-edgeai-import-model

Get a trained neural network that exports to a static-shape ONNX (a classifier, a segmentation model, or a detector with a TIDL meta-architecture such as YOLOX/SSD/YOLOv5-style) running on a TI Edge AI board's C7x/MMA accelerator (TDA4VM, AM68A, AM69A, AM67A, AM62A): preflight the ONNX, fold input normalisation, compile and int8-calibrate with edgeai-tidl-tools in Docker (tools tag matched to the board SDK), verify offload and accuracy in host emulation, check board-vs-host outputs, package model/ artifacts/ param.yaml dataset.yaml, deploy to /opt/model_zoo and smoke-test with edgeai-gst-apps. Use this skill whenever the user wants to deploy, convert, compile, quantize, port or "put my model on" a TI Jacinto/AM6xA board, mentions TIDL compilation, artifacts, tidl_net.bin, meta_arch_type, a prototxt, calibration images, int8 accuracy loss on the TI device, or asks why a compiled model fails on the board - for any architecture within those contracts, and even if they only say "deploy to the TI device".

Version

0.1.0

License

MIT