DETR-ResNet50-DC5: Optimized for Qualcomm Devices

DETR is a machine learning model that can detect objects (trained on COCO dataset).

This is based on the implementation of DETR-ResNet50-DC5 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 1.24.1	Download
QNN_DLC	float	Universal	QAIRT 2.43	Download
TFLITE	float	Universal	QAIRT 2.43, TFLite 2.17.0	Download

For more device-specific assets and performance metrics, visit DETR-ResNet50-DC5 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 DETR-ResNet50-DC5 on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.object_detection

Model Stats:

• Model checkpoint: ResNet50-DC5
• Input resolution: 480x480
• Model size (float): 160 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
DETR-ResNet50-DC5	ONNX	float	Snapdragon® X2 Elite	20.302 ms	79 - 79 MB	NPU
DETR-ResNet50-DC5	ONNX	float	Snapdragon® X Elite	45.406 ms	78 - 78 MB	NPU
DETR-ResNet50-DC5	ONNX	float	Snapdragon® 8 Gen 3 Mobile	32.511 ms	2 - 642 MB	NPU
DETR-ResNet50-DC5	ONNX	float	Qualcomm® QCS8550 (Proxy)	44.622 ms	0 - 95 MB	NPU
DETR-ResNet50-DC5	ONNX	float	Qualcomm® QCS9075	64.675 ms	5 - 12 MB	NPU
DETR-ResNet50-DC5	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	23.603 ms	3 - 420 MB	NPU
DETR-ResNet50-DC5	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	18.957 ms	5 - 474 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Snapdragon® X2 Elite	20.76 ms	5 - 5 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Snapdragon® X Elite	47.595 ms	5 - 5 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	33.925 ms	5 - 629 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Qualcomm® QCS8275 (Proxy)	171.904 ms	1 - 478 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	46.548 ms	5 - 7 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Qualcomm® SA8775P	60.101 ms	1 - 477 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Qualcomm® QCS9075	69.754 ms	5 - 11 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	74.725 ms	3 - 450 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Qualcomm® SA7255P	171.904 ms	1 - 478 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Qualcomm® SA8295P	63.396 ms	0 - 325 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	24.281 ms	5 - 502 MB	NPU
DETR-ResNet50-DC5	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	19.169 ms	5 - 507 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	32.355 ms	0 - 652 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Qualcomm® QCS8275 (Proxy)	168.929 ms	0 - 515 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Qualcomm® QCS8550 (Proxy)	44.04 ms	0 - 3 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Qualcomm® SA8775P	58.046 ms	0 - 512 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Qualcomm® QCS9075	65.915 ms	0 - 90 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Qualcomm® QCS8450 (Proxy)	79.383 ms	0 - 477 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Qualcomm® SA7255P	168.929 ms	0 - 515 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Qualcomm® SA8295P	65.362 ms	0 - 382 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	22.489 ms	0 - 544 MB	NPU
DETR-ResNet50-DC5	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	17.741 ms	0 - 536 MB	NPU

License

• The license for the original implementation of DETR-ResNet50-DC5 can be found here.

References

• End-to-End Object Detection with Transformers
• 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.