RF-DETR: 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 RF-DETR 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 2.50, ONNX Runtime 1.27.1 | Download |
| QNN_DLC | float | Universal | QAIRT 2.50 | Download |
For more device-specific assets and performance metrics, visit RF-DETR 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 RF-DETR on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.object_detection
Model Stats:
- Input resolution: 512x512
- Model checkpoint: RF-DETR-small
- Model size (float): 109 MB
- Number of parameters: 28.5M
- Supported variants: nano (384x384), small (512x512), medium (576x576), base (560x560)
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| RF-DETR | ONNX | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 19.505 ms | 11 - 305 MB | NPU |
| RF-DETR | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 22.043 ms | 12 - 307 MB | NPU |
| RF-DETR | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 30.993 ms | 0 - 404 MB | NPU |
| RF-DETR | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 72.724 ms | 0 - 411 MB | NPU |
| RF-DETR | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 49.863 ms | 9 - 16 MB | NPU |
| RF-DETR | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 39.871 ms | 11 - 180 MB | NPU |
| RF-DETR | ONNX | float | Qualcomm® QCS8450 | 72.724 ms | 0 - 411 MB | NPU |
| RF-DETR | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 49.276 ms | 10 - 17 MB | NPU |
| RF-DETR | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 22.043 ms | 12 - 307 MB | NPU |
| RF-DETR | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 18.542 ms | 3 - 337 MB | NPU |
| RF-DETR | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 21.8 ms | 3 - 333 MB | NPU |
| RF-DETR | QNN_DLC | float | Snapdragon® X2 Elite | 19.734 ms | 3 - 3 MB | NPU |
| RF-DETR | QNN_DLC | float | Snapdragon® X Elite | 42.036 ms | 3 - 3 MB | NPU |
| RF-DETR | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 28.9 ms | 0 - 447 MB | NPU |
| RF-DETR | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 73.945 ms | 0 - 449 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 47.213 ms | 3 - 9 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 40.361 ms | 3 - 304 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® SA8775P | 47.454 ms | 0 - 330 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® SA8650P | 47.454 ms | 0 - 330 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® SA8255P | 47.454 ms | 0 - 330 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® QCS8450 | 73.945 ms | 0 - 449 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 47.716 ms | 3 - 8 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 42.036 ms | 3 - 3 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 21.8 ms | 3 - 333 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® SA7255P | 120.712 ms | 1 - 337 MB | NPU |
| RF-DETR | QNN_DLC | float | Qualcomm® SA8295P | 69.05 ms | 0 - 340 MB | NPU |
License
- The license for the original implementation of RF-DETR can be found here.
References
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.
