mlboydaisuke / RTMPose-m-Animal-ExecuTorch

huggingface.co
Total runs: 37
24-hour runs: 0
7-day runs: -8
30-day runs: -17
Model's Last Updated: August 20 2026
keypoint-detection

Introduction of RTMPose-m-Animal-ExecuTorch

Model Details of RTMPose-m-Animal-ExecuTorch

rtmpose_m_animal — ExecuTorch

  • Source : open-mmlab/mmpose RTMPose (rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1)
  • License : Apache-2.0
  • Input : [[1, 3, 256, 256]] — RGB, ImageNet norm, 256x256 crop around an animal (detect first, then crop and resize to this aspect)
  • Output : SimCC pair: x [1,17,512] and y [1,17,512] — a 1-D distribution per keypoint per axis. Decode: keypoint k sits at (argmax(x[k]) / 2, argmax(y[k]) / 2) in crop pixels; the max value doubles as the confidence.
Variants

All variants take and return fp32 tensors — swap the .pte file, keep your app code.

build file size (MB) parity vs fp32 eager (worst corr) Mac median (ms)*
fp32 rtmpose_m_animal_xnnpack_fp32.pte 54.5 1.000000 9.4

*Mac arm64, single process, median of 10 — a reference point for relative cost only, not a device number (torch eager fp32 on the same machine: 91.4 ms).

Builds that did not earn a slot
  • Core ML (fp16, iOS) is not shipped : measured in the units that matter for this model — fraction of keypoints landing within 4 px of fp32: median 0.9412 over 10 real images, worst 0.7647.
Verification (executorch 1.4.0, torch 2.13.0)

Parity is measured against the fp32 eager model on real image input; corr is the correlation over all elements of each output tensor.

output shape max_abs_diff corr
0 [1, 17, 512] 2.783e-06 1.000000
1 [1, 17, 512] 7.629e-06 1.000000

XNNPACK delegate coverage (fp32): 93.9% (306/326 ops); ops left on the portable kernels: dim_order_ops._to_dim_order_copy.default x8, aten.unsqueeze_copy.default x3, aten.split_with_sizes_copy.default x3, aten.sum.dim_IntList x2, aten.pow.Tensor_Scalar x2, aten.squeeze_copy.dims x2

Conversion

torch.export -> to_edge_transform_and_lower(partitioner) -> .pte (conversion scripts: executorch-models )

Notes : Top-down again: crop one animal first. AP-10K covers 54 mammal species; a general object detector's animal classes make a workable front end.


More models in this format: ExecuTorch Model Zoo — 31 models, each with the recipe that produced it.

Want a different model on-device? Open a request — free, open weights only; the export and its measured numbers get published publicly.

Runs of mlboydaisuke RTMPose-m-Animal-ExecuTorch on huggingface.co

37
Total runs
0
24-hour runs
-7
3-day runs
-8
7-day runs
-17
30-day runs

More Information About RTMPose-m-Animal-ExecuTorch huggingface.co Model

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RTMPose-m-Animal-ExecuTorch install

RTMPose-m-Animal-ExecuTorch is an open source model from GitHub that offers a free installation service, and any user can find RTMPose-m-Animal-ExecuTorch on GitHub to install. At the same time, huggingface.co provides the effect of RTMPose-m-Animal-ExecuTorch install, users can directly use RTMPose-m-Animal-ExecuTorch installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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