DETR-ResNet101-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-ResNet101-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 2.45, ONNX Runtime 1.27.1 | Download |
| QNN_DLC | float | Universal | QAIRT 2.45 | Download |
| TFLITE | float | Universal | QAIRT 2.45 | Download |
For more device-specific assets and performance metrics, visit DETR-ResNet101-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-ResNet101-DC5 on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.object_detection
Model Stats:
- Model checkpoint: ResNet101-DC5
- Input resolution: 480x480
- Model size (float): 232 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® X2 Elite | 23.617 ms | 5 - 5 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® X Elite | 51.355 ms | 115 - 115 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 36.478 ms | 5 - 575 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 84.27 ms | 0 - 478 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 49.721 ms | 5 - 7 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® QCS8450 | 84.27 ms | 0 - 478 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 68.853 ms | 5 - 12 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 51.355 ms | 115 - 115 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 27.287 ms | 2 - 436 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® 8 Elite Mobile | 27.287 ms | 2 - 436 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 21.773 ms | 3 - 445 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® X2 Elite | 24.921 ms | 5 - 5 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® X Elite | 53.27 ms | 5 - 5 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 37.538 ms | 5 - 556 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 108.927 ms | 5 - 469 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8275 | 220.397 ms | 2 - 427 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 51.38 ms | 5 - 7 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA8775P | 69.887 ms | 1 - 427 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA8650P | 69.887 ms | 1 - 427 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA8255P | 69.887 ms | 1 - 427 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® QCS8450 | 108.927 ms | 5 - 469 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 69.638 ms | 7 - 13 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 53.27 ms | 5 - 5 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 28.135 ms | 0 - 450 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA7255P | 220.397 ms | 2 - 427 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA8295P | 86.058 ms | 1 - 342 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 28.135 ms | 0 - 450 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 22.662 ms | 5 - 450 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 37.198 ms | 0 - 599 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 84.692 ms | 1 - 478 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® Dragonwing™ QCS8275 | 219.41 ms | 0 - 471 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 50.75 ms | 0 - 4 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA8775P | 69.558 ms | 0 - 470 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA8650P | 69.558 ms | 0 - 470 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA8255P | 69.558 ms | 0 - 470 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® QCS8450 | 84.692 ms | 1 - 478 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 78.078 ms | 0 - 126 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 27.746 ms | 0 - 476 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA7255P | 219.41 ms | 0 - 471 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA8295P | 76.615 ms | 0 - 358 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Snapdragon® 8 Elite Mobile | 27.746 ms | 0 - 476 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 22.313 ms | 0 - 494 MB | NPU |
License
- The license for the original implementation of DETR-ResNet101-DC5 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.
