Yolo-R: Optimized for Qualcomm Devices

YoloR is a machine learning model that predicts bounding boxes and classes of objects in an image.

This is based on the implementation of Yolo-R 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

Due to licensing restrictions, we cannot distribute pre-exported model assets for this model. 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

See our repository for Yolo-R on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.object_detection

Model Stats:

• Model checkpoint: yolor_p6
• Input resolution: 640x640
• Number of parameters: 4.68M
• Model size (float): 17.9 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
Yolo-R	ONNX	float	Snapdragon® X2 Elite	26.79 ms	5 - 5 MB	NPU
Yolo-R	ONNX	float	Snapdragon® X Elite	40.751 ms	75 - 75 MB	NPU
Yolo-R	ONNX	float	Snapdragon® 8 Gen 3 Mobile	31.447 ms	0 - 331 MB	NPU
Yolo-R	ONNX	float	Snapdragon® 8 Gen 1 Mobile	92.147 ms	6 - 524 MB	NPU
Yolo-R	ONNX	float	Qualcomm® Dragonwing™ QCS8550 (Proxy)	40.026 ms	5 - 8 MB	NPU
Yolo-R	ONNX	float	Qualcomm® QCS8450	92.147 ms	6 - 524 MB	NPU
Yolo-R	ONNX	float	Qualcomm® Dragonwing™ IQ-9075	47.694 ms	5 - 12 MB	NPU
Yolo-R	ONNX	float	Qualcomm® Dragonwing™ IQ-X7181	40.751 ms	75 - 75 MB	NPU
Yolo-R	ONNX	float	Qualcomm® Dragonwing™ Q-8750	28.044 ms	3 - 233 MB	NPU
Yolo-R	ONNX	float	Snapdragon® 8 Elite Mobile	28.044 ms	3 - 233 MB	NPU
Yolo-R	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	27.585 ms	3 - 295 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® X2 Elite	19.175 ms	2 - 2 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® X Elite	30.831 ms	41 - 41 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® 8 Gen 3 Mobile	20.922 ms	1 - 464 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® 8 Gen 1 Mobile	42.424 ms	3 - 461 MB	NPU
Yolo-R	ONNX	w8a16	Qualcomm® Dragonwing™ QCS8550 (Proxy)	29.41 ms	2 - 6 MB	NPU
Yolo-R	ONNX	w8a16	Qualcomm® QCS8450	42.424 ms	3 - 461 MB	NPU
Yolo-R	ONNX	w8a16	Qualcomm® Dragonwing™ IQ-9075	30.957 ms	1 - 6 MB	NPU
Yolo-R	ONNX	w8a16	Qualcomm® Dragonwing™ IQ-X7181	30.831 ms	41 - 41 MB	NPU
Yolo-R	ONNX	w8a16	Qualcomm® Dragonwing™ Q-8750	17.867 ms	2 - 365 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® 8 Elite Mobile	17.867 ms	2 - 365 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	18.762 ms	1 - 425 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® X2 Elite	8.641 ms	2 - 2 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® X Elite	19.509 ms	2 - 2 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 8 Gen 3 Mobile	12.447 ms	2 - 356 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 8 Gen 1 Mobile	28.046 ms	2 - 358 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® Dragonwing™ QCS6490	91.189 ms	2 - 7 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® Dragonwing™ QCS8275	37.802 ms	2 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® Dragonwing™ QCS8550 (Proxy)	18.513 ms	2 - 4 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA8775P	18.744 ms	1 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA8650P	18.744 ms	1 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA8255P	18.744 ms	1 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® QCS8450	28.046 ms	2 - 358 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® Dragonwing™ IQ-9075	18.861 ms	0 - 4 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® Dragonwing™ IQ-X7181	19.509 ms	2 - 2 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® Dragonwing™ Q-6690	219.672 ms	2 - 399 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® Dragonwing™ Q-7790	25.965 ms	2 - 309 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® Dragonwing™ Q-8750	9.391 ms	2 - 304 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA7255P	37.802 ms	2 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA8295P	24.277 ms	0 - 292 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 8 Elite Mobile	9.391 ms	2 - 304 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	7.859 ms	2 - 310 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	25.965 ms	2 - 309 MB	NPU

License

• The license for the original implementation of Yolo-R can be found here.

References

• You Only Learn One Representation: Unified Network for Multiple Tasks
• 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.