Conditional-DETR-ResNet50: 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 Conditional-DETR-ResNet50 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 |
| ONNX | w8a16 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| QNN_DLC | float | Universal | QAIRT 2.43 | Download |
| QNN_DLC | w8a16 | 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 Conditional-DETR-ResNet50 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 Conditional-DETR-ResNet50 on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.object_detection
Model Stats:
- Model checkpoint: ResNet50
- Input resolution: 480x480
- Number of parameters: 43.6M
- Model size (float): 166 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® X2 Elite | 8.836 ms | 82 - 82 MB | NPU |
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® X Elite | 19.884 ms | 81 - 81 MB | NPU |
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 14.924 ms | 1 - 476 MB | NPU |
| Conditional-DETR-ResNet50 | ONNX | float | Qualcomm® QCS8550 (Proxy) | 19.763 ms | 0 - 96 MB | NPU |
| Conditional-DETR-ResNet50 | ONNX | float | Qualcomm® QCS9075 | 30.848 ms | 5 - 12 MB | NPU |
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 10.98 ms | 2 - 397 MB | NPU |
| Conditional-DETR-ResNet50 | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 8.364 ms | 5 - 406 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® X2 Elite | 10.347 ms | 5 - 5 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® X Elite | 23.183 ms | 5 - 5 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 16.764 ms | 0 - 426 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 97.911 ms | 1 - 324 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 22.797 ms | 5 - 7 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® SA8775P | 32.053 ms | 0 - 325 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS9075 | 34.054 ms | 5 - 11 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 46.248 ms | 4 - 374 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® SA7255P | 97.911 ms | 1 - 324 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Qualcomm® SA8295P | 34.268 ms | 0 - 282 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 11.564 ms | 5 - 341 MB | NPU |
| Conditional-DETR-ResNet50 | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 8.797 ms | 5 - 347 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 16.94 ms | 0 - 464 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 92.842 ms | 0 - 363 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 22.429 ms | 0 - 3 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® SA8775P | 30.187 ms | 0 - 423 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® QCS9075 | 33.586 ms | 0 - 93 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 45.538 ms | 0 - 404 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® SA7255P | 92.842 ms | 0 - 363 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Qualcomm® SA8295P | 34.36 ms | 0 - 311 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 11.909 ms | 0 - 375 MB | NPU |
| Conditional-DETR-ResNet50 | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 9.315 ms | 0 - 380 MB | NPU |
License
- The license for the original implementation of Conditional-DETR-ResNet50 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.
