
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:
- Input resolution: 480x480
- Model checkpoint: ResNet101-DC5
- 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 | 23.625 ms | 5 - 5 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® X Elite | 51.34 ms | 115 - 115 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 36.41 ms | 5 - 572 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 84.556 ms | 1 - 476 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 72.506 ms | 5 - 13 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 49.717 ms | 0 - 127 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® QCS8450 | 84.556 ms | 1 - 476 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 68.977 ms | 5 - 12 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 51.34 ms | 115 - 115 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 27.174 ms | 3 - 436 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® 8 Elite Mobile | 27.174 ms | 3 - 436 MB | NPU |
| DETR-ResNet101-DC5 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 21.756 ms | 1 - 446 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® X2 Elite | 24.72 ms | 5 - 5 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® X Elite | 53.521 ms | 5 - 5 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 37.618 ms | 2 - 553 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 108.871 ms | 5 - 468 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 73.503 ms | 5 - 12 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 51.201 ms | 5 - 7 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA8775P | 69.864 ms | 0 - 426 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA8650P | 69.864 ms | 0 - 426 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA8255P | 69.864 ms | 0 - 426 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® QCS8450 | 108.871 ms | 5 - 468 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 69.742 ms | 5 - 11 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 53.521 ms | 5 - 5 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 27.982 ms | 5 - 453 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA7255P | 220.255 ms | 1 - 426 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Qualcomm® SA8295P | 86.104 ms | 2 - 343 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 27.982 ms | 5 - 453 MB | NPU |
| DETR-ResNet101-DC5 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 22.645 ms | 5 - 449 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 37.26 ms | 0 - 599 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 84.498 ms | 1 - 479 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 73.019 ms | 0 - 127 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 50.767 ms | 0 - 3 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA8775P | 69.524 ms | 0 - 470 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA8650P | 69.524 ms | 0 - 470 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA8255P | 69.524 ms | 0 - 470 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® QCS8450 | 84.498 ms | 1 - 479 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 69.79 ms | 0 - 126 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 27.966 ms | 0 - 480 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA7255P | 219.47 ms | 1 - 472 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Qualcomm® SA8295P | 76.612 ms | 0 - 358 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Snapdragon® 8 Elite Mobile | 27.966 ms | 0 - 480 MB | NPU |
| DETR-ResNet101-DC5 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 22.281 ms | 0 - 493 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.