Instructions to use litert-community/lightweight-openpose with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/lightweight-openpose with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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Browse files
README.md
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@@ -19,6 +19,8 @@ On-device [LiteRT](https://ai.google.dev/edge/litert) (`.tflite`) conversion of
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for human pose estimation. The model is a MobileNet-based heatmap network; it outputs
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**keypoint heatmaps only** and the keypoint decode (argmax) is done in app code.
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The model runs **fully on the LiteRT `CompiledModel` GPU accelerator** (ML Drift): every op is
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GPU-native, no CPU fallback. Converted with
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[`litert-torch`](https://github.com/google-ai-edge/ai-edge-torch) **with no patches**.
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for human pose estimation. The model is a MobileNet-based heatmap network; it outputs
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**keypoint heatmaps only** and the keypoint decode (argmax) is done in app code.
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The model runs **fully on the LiteRT `CompiledModel` GPU accelerator** (ML Drift): every op is
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GPU-native, no CPU fallback. Converted with
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[`litert-torch`](https://github.com/google-ai-edge/ai-edge-torch) **with no patches**.
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