HFNet: Optimized for Qualcomm Devices
HFNet provides local keypoints and descriptors together with a global descriptor for image matching and localization pipelines.
This is based on the implementation of HFNet 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 1.30.0 | Download |
| QNN_DLC | float | Universal | QAIRT 2.50 | Download |
| TFLITE | float | Universal | QAIRT 2.50 | Download |
For more device-specific assets and performance metrics, visit HFNet 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 HFNet on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.robotics
Model Stats:
- Input format: NHWC float32, range 0..255
- Input resolution: 640x480 (grayscale)
- Model size (float): 126MB
- Number of parameters: 33.0M
- Outputs: Global descriptor, keypoints, keypoint scores, dense scores
- Source model: hfnet.onnx
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| HFNet | ONNX | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 67.148 ms | 8 - 218 MB | NPU |
| HFNet | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 69.305 ms | 10 - 208 MB | NPU |
| HFNet | ONNX | float | Snapdragon® X2 Elite | 67.013 ms | 16 - 16 MB | NPU |
| HFNet | ONNX | float | Snapdragon® X Elite | 117.702 ms | 66 - 66 MB | NPU |
| HFNet | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 81.859 ms | 0 - 316 MB | NPU |
| HFNet | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 119.598 ms | 0 - 312 MB | NPU |
| HFNet | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 104.8 ms | 8 - 13 MB | NPU |
| HFNet | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 117.978 ms | 0 - 81 MB | NPU |
| HFNet | ONNX | float | Qualcomm® QCS8450 | 119.598 ms | 0 - 312 MB | NPU |
| HFNet | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 119.424 ms | 9 - 14 MB | NPU |
| HFNet | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 117.702 ms | 66 - 66 MB | NPU |
| HFNet | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 69.305 ms | 10 - 208 MB | NPU |
| HFNet | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 65.291 ms | 1 - 217 MB | NPU |
| HFNet | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 69.375 ms | 2 - 206 MB | NPU |
| HFNet | QNN_DLC | float | Snapdragon® X2 Elite | 68.248 ms | 1 - 1 MB | NPU |
| HFNet | QNN_DLC | float | Snapdragon® X Elite | 118.775 ms | 1 - 1 MB | NPU |
| HFNet | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 81.774 ms | 0 - 313 MB | NPU |
| HFNet | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 120.393 ms | 1 - 311 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 104.206 ms | 1 - 9 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 116.944 ms | 1 - 3 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® SA8775P | 119.88 ms | 2 - 198 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® SA8650P | 119.88 ms | 2 - 198 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® SA8255P | 119.88 ms | 2 - 198 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® QCS8450 | 120.393 ms | 1 - 311 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 118.929 ms | 1 - 8 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 118.775 ms | 1 - 1 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 69.375 ms | 2 - 206 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® SA7255P | 184.735 ms | 1 - 196 MB | NPU |
| HFNet | QNN_DLC | float | Qualcomm® SA8295P | 128.435 ms | 2 - 201 MB | NPU |
| HFNet | TFLITE | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 67.176 ms | 2 - 214 MB | NPU |
| HFNet | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 68.351 ms | 0 - 204 MB | NPU |
| HFNet | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 82.476 ms | 4 - 327 MB | NPU |
| HFNet | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 122.661 ms | 4 - 323 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 104.369 ms | 4 - 78 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 119.124 ms | 0 - 88 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® SA8775P | 120.633 ms | 4 - 207 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® SA8650P | 120.633 ms | 4 - 207 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® SA8255P | 120.633 ms | 4 - 207 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® QCS8450 | 122.661 ms | 4 - 323 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 121.005 ms | 4 - 77 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 68.351 ms | 0 - 204 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® SA7255P | 184.775 ms | 4 - 207 MB | NPU |
| HFNet | TFLITE | float | Qualcomm® SA8295P | 130.442 ms | 4 - 207 MB | NPU |
License
- The license for the original implementation of HFNet can be found here.
References
- HF-Net: Combining Hierarchical Local and Global Features for Visual Localization
- 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.
