[Example] Yolo12 Detection sample with OpenVINO/XNNPACK backend

[daniil-lyakhov]

Summary

Ultralytics Yolo12 Detection sample to expand example models with the detection task:

1. Export script to get executorch yolo model lowered to OpenVINO/XNNPACK
2. Demo app which gets a model and a video as an input and outputs an annotated video

Changes in the OpenVINO backend:

• OpenVINO repo branch is updated to support yolo12 models (Commit to Openvino master WIP)
• Minor fixes in quantizer.py

Test plan

Warning:

OpenCV should be installed in the environment.

OpenVINO:

./.ci/scripts/test_yolo12.sh  -model yolo12n -mode openvino -pt2e_quantize OFF -upload tmp_ov_run -video_path  path/to/mp4/file

XNNPACK:

./.ci/scripts/test_yolo12.sh  -model yolo12n -mode xnnpack -pt2e_quantize OFF -upload tmp_xnnpack_run -video_path  path/to/mp4/file

Issues:

• Quantization does not work in both backends, issues WIP. Marked by NonImplemented error by now
• OpenVINO is being build twice because it is not present in the executorch-config.cmake file. Perhaps we could add the OpenVINO backend to the config file?

CC: @ynimmaga @suryasidd @alexsu52

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/10156

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[GregoryComer]

FYI On the mlock error, you can try switching the load mode in the Module constructor (or data loader) to Mmap (from Mlock). IMO that should be the default.

[alexsu52]

I think some sanity checking needs to be added to this example.

[alexsu52]

Could you manage subgraphs without changing the function signature?

[daniil-lyakhov]

Done

[daniil-lyakhov]

FYI On the mlock error, you can try switching the load mode in the Module constructor (or data loader) to Mmap (from Mlock). IMO that should be the default.

This helped, thanks!

[daniil-lyakhov]

@lucylq, @jackzhxng, could you please take a look?