RTMPose-Body2d: Optimized for Qualcomm Devices

RTMPose is a machine learning model that detects human pose and returns a location and confidence for each of 133 joints.

This is based on the implementation of RTMPose-Body2d found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.

Getting Started

There are two ways to deploy this model on your device:

Option 1: Download Pre-Exported Models

Below are pre-exported model assets ready for deployment.

Runtime	Precision	Chipset	SDK Versions	Download
ONNX	float	Universal	QAIRT 2.42, ONNX Runtime 1.24.3	Download
ONNX	w8a16	Universal	QAIRT 2.42, ONNX Runtime 1.24.3	Download
QNN_DLC	float	Universal	QAIRT 2.43	Download
QNN_DLC	w8a16	Universal	QAIRT 2.43	Download
TFLITE	float	Universal	QAIRT 2.43, TFLite 2.19.1	Download

For more device-specific assets and performance metrics, visit RTMPose-Body2d on Qualcomm® AI Hub.

Option 2: Export with Custom Configurations

Use the Qualcomm® AI Hub Models Python library to compile and export the model with your own:

• Custom weights (e.g., fine-tuned checkpoints)
• Custom input shapes
• Target device and runtime configurations

This option is ideal if you need to customize the model beyond the default configuration provided here.

See our repository for RTMPose-Body2d on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.pose_estimation

Model Stats:

• Input resolution: 256x192
• Number of parameters: 17.9M
• Model size (float): 68.5 MB
• Model size (w8a16): 18.2 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
RTMPose-Body2d	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	0.922 ms	0 - 40 MB	NPU
RTMPose-Body2d	ONNX	float	Snapdragon® X2 Elite	0.937 ms	37 - 37 MB	NPU
RTMPose-Body2d	ONNX	float	Snapdragon® X Elite	1.851 ms	37 - 37 MB	NPU
RTMPose-Body2d	ONNX	float	Snapdragon® 8 Gen 3 Mobile	1.343 ms	0 - 56 MB	NPU
RTMPose-Body2d	ONNX	float	Qualcomm® QCS8550 (Proxy)	1.78 ms	0 - 171 MB	NPU
RTMPose-Body2d	ONNX	float	Qualcomm® QCS9075	2.431 ms	0 - 4 MB	NPU
RTMPose-Body2d	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	1.091 ms	0 - 36 MB	NPU
RTMPose-Body2d	ONNX	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	0.739 ms	0 - 60 MB	NPU
RTMPose-Body2d	ONNX	w8a16	Snapdragon® X2 Elite	0.771 ms	19 - 19 MB	NPU
RTMPose-Body2d	ONNX	w8a16	Snapdragon® X Elite	1.93 ms	19 - 19 MB	NPU
RTMPose-Body2d	ONNX	w8a16	Snapdragon® 8 Gen 3 Mobile	1.172 ms	0 - 92 MB	NPU
RTMPose-Body2d	ONNX	w8a16	Qualcomm® QCS6490	163.105 ms	48 - 51 MB	CPU
RTMPose-Body2d	ONNX	w8a16	Qualcomm® QCS8550 (Proxy)	1.71 ms	0 - 149 MB	NPU
RTMPose-Body2d	ONNX	w8a16	Qualcomm® QCS9075	1.909 ms	0 - 3 MB	NPU
RTMPose-Body2d	ONNX	w8a16	Qualcomm® QCM6690	86.821 ms	47 - 55 MB	CPU
RTMPose-Body2d	ONNX	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	0.861 ms	0 - 54 MB	NPU
RTMPose-Body2d	ONNX	w8a16	Snapdragon® 7 Gen 4 Mobile	82.562 ms	48 - 57 MB	CPU
RTMPose-Body2d	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	0.905 ms	1 - 36 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Snapdragon® X2 Elite	1.09 ms	1 - 1 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Snapdragon® X Elite	1.845 ms	1 - 1 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	1.317 ms	0 - 58 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Qualcomm® QCS8275 (Proxy)	7.536 ms	1 - 33 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	1.747 ms	1 - 2 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Qualcomm® SA8775P	2.447 ms	1 - 35 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Qualcomm® QCS9075	2.413 ms	1 - 3 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	3.524 ms	0 - 63 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Qualcomm® SA7255P	7.536 ms	1 - 33 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Qualcomm® SA8295P	3.543 ms	0 - 35 MB	NPU
RTMPose-Body2d	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	1.09 ms	1 - 36 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	0.751 ms	0 - 51 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Snapdragon® X2 Elite	0.965 ms	0 - 0 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Snapdragon® X Elite	1.958 ms	0 - 0 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Snapdragon® 8 Gen 3 Mobile	1.162 ms	0 - 79 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Qualcomm® QCS8275 (Proxy)	3.849 ms	0 - 49 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Qualcomm® QCS8550 (Proxy)	1.736 ms	0 - 2 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Qualcomm® SA8775P	2.05 ms	0 - 53 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Qualcomm® QCS9075	1.905 ms	2 - 4 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Qualcomm® SA7255P	3.849 ms	0 - 49 MB	NPU
RTMPose-Body2d	QNN_DLC	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	0.893 ms	0 - 50 MB	NPU
RTMPose-Body2d	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	0.894 ms	0 - 51 MB	NPU
RTMPose-Body2d	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	1.27 ms	0 - 88 MB	NPU
RTMPose-Body2d	TFLITE	float	Qualcomm® QCS8275 (Proxy)	7.471 ms	0 - 48 MB	NPU
RTMPose-Body2d	TFLITE	float	Qualcomm® QCS8550 (Proxy)	1.736 ms	0 - 2 MB	NPU
RTMPose-Body2d	TFLITE	float	Qualcomm® SA8775P	2.447 ms	0 - 50 MB	NPU
RTMPose-Body2d	TFLITE	float	Qualcomm® QCS9075	2.397 ms	0 - 40 MB	NPU
RTMPose-Body2d	TFLITE	float	Qualcomm® QCS8450 (Proxy)	3.546 ms	0 - 99 MB	NPU
RTMPose-Body2d	TFLITE	float	Qualcomm® SA7255P	7.471 ms	0 - 48 MB	NPU
RTMPose-Body2d	TFLITE	float	Qualcomm® SA8295P	3.539 ms	0 - 51 MB	NPU
RTMPose-Body2d	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	1.088 ms	0 - 52 MB	NPU

License

• The license for the original implementation of RTMPose-Body2d can be found here.

References

• RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose
• Source Model Implementation

Community

• Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
• For questions or feedback please reach out to us.