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® 8 Elite Gen 5 Mobile	24.445 ms	6 - 316 MB	NPU
Yolo-R	ONNX	float	Snapdragon® 8 Elite Mobile	25.096 ms	2 - 232 MB	NPU
Yolo-R	ONNX	float	Snapdragon® X2 Elite	24.767 ms	75 - 75 MB	NPU
Yolo-R	ONNX	float	Snapdragon® X Elite	38.214 ms	74 - 74 MB	NPU
Yolo-R	ONNX	float	Snapdragon® X Elite	38.214 ms	74 - 74 MB	NPU
Yolo-R	ONNX	float	Snapdragon® 8 Gen 3 Mobile	28.964 ms	0 - 341 MB	NPU
Yolo-R	ONNX	float	Qualcomm® QCS8550 (Proxy)	38.039 ms	0 - 78 MB	NPU
Yolo-R	ONNX	float	Qualcomm® QCS9075	52.16 ms	5 - 12 MB	NPU
Yolo-R	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	25.096 ms	2 - 232 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	18.066 ms	3 - 452 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® 8 Elite Mobile	17.404 ms	1 - 366 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® X2 Elite	18.504 ms	41 - 41 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® X Elite	30.398 ms	40 - 40 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® X Elite	30.398 ms	40 - 40 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® 8 Gen 3 Mobile	20.837 ms	0 - 492 MB	NPU
Yolo-R	ONNX	w8a16	Qualcomm® QCS6490	2272.484 ms	129 - 135 MB	CPU
Yolo-R	ONNX	w8a16	Qualcomm® QCS8550 (Proxy)	29.064 ms	0 - 49 MB	NPU
Yolo-R	ONNX	w8a16	Qualcomm® QCS9075	29.698 ms	1 - 6 MB	NPU
Yolo-R	ONNX	w8a16	Qualcomm® QCM6690	1177.534 ms	91 - 103 MB	CPU
Yolo-R	ONNX	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	17.404 ms	1 - 366 MB	NPU
Yolo-R	ONNX	w8a16	Snapdragon® 7 Gen 4 Mobile	1120.199 ms	136 - 148 MB	CPU
Yolo-R	ONNX	w8a16	Snapdragon® 7 Gen 4 Mobile	1120.199 ms	136 - 148 MB	CPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	7.916 ms	2 - 305 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 8 Elite Mobile	10.167 ms	2 - 304 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® X2 Elite	8.914 ms	2 - 2 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® X Elite	20.753 ms	2 - 2 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® X Elite	20.753 ms	2 - 2 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 8 Gen 3 Mobile	13.32 ms	2 - 356 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® QCS6490	78.992 ms	1 - 6 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® QCS8275 (Proxy)	39.816 ms	2 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® QCS8550 (Proxy)	19.887 ms	2 - 272 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA8775P	19.89 ms	2 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA8775P	19.89 ms	2 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA8775P	19.89 ms	2 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® QCS9075	20.74 ms	1 - 6 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® QCM6690	214.15 ms	2 - 400 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® QCS8450 (Proxy)	28.632 ms	2 - 358 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA7255P	39.816 ms	2 - 291 MB	NPU
Yolo-R	QNN_DLC	w8a16	Qualcomm® SA8295P	25.586 ms	0 - 293 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	10.167 ms	2 - 304 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	26.722 ms	2 - 318 MB	NPU
Yolo-R	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	26.722 ms	2 - 318 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.