Facial-Landmark-Detection: Optimized for Qualcomm Devices
Detects facial landmarks (eg, nose, mouth, etc.). This model's architecture was developed by Qualcomm. The model was trained by Qualcomm on a proprietary dataset of faces, but can be used on any image.
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 | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | Download |
| QNN_DLC | float | Universal | QAIRT 2.43 | Download |
| QNN_DLC | w8a8 | Universal | QAIRT 2.43 | Download |
| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | Download |
| TFLITE | w8a8 | Universal | QAIRT 2.43, TFLite 2.17.0 | Download |
For more device-specific assets and performance metrics, visit Facial-Landmark-Detection 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 Facial-Landmark-Detection on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.pose_estimation
Model Stats:
- Input resolution: 128x128
- Number of parameters: 5.42M
- Model size (float): 20.7 MB
- Model size (w8a8): 5.27 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| Facial-Landmark-Detection | ONNX | float | Snapdragon® X2 Elite | 0.206 ms | 10 - 10 MB | NPU |
| Facial-Landmark-Detection | ONNX | float | Snapdragon® X Elite | 0.394 ms | 10 - 10 MB | NPU |
| Facial-Landmark-Detection | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.246 ms | 0 - 30 MB | NPU |
| Facial-Landmark-Detection | ONNX | float | Qualcomm® QCS8550 (Proxy) | 0.319 ms | 0 - 14 MB | NPU |
| Facial-Landmark-Detection | ONNX | float | Qualcomm® QCS9075 | 0.437 ms | 0 - 3 MB | NPU |
| Facial-Landmark-Detection | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.223 ms | 0 - 19 MB | NPU |
| Facial-Landmark-Detection | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.211 ms | 0 - 23 MB | NPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® X2 Elite | 0.071 ms | 5 - 5 MB | NPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® X Elite | 0.25 ms | 5 - 5 MB | NPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.14 ms | 0 - 37 MB | NPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Qualcomm® QCS6490 | 2.929 ms | 0 - 7 MB | CPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.171 ms | 0 - 2 MB | NPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Qualcomm® QCS9075 | 0.258 ms | 0 - 3 MB | NPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Qualcomm® QCM6690 | 1.711 ms | 0 - 7 MB | CPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.124 ms | 0 - 24 MB | NPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.274 ms | 0 - 6 MB | CPU |
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.11 ms | 0 - 23 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® X2 Elite | 0.232 ms | 0 - 0 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® X Elite | 0.375 ms | 0 - 0 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.23 ms | 0 - 30 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 1.117 ms | 0 - 21 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 0.288 ms | 0 - 58 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® SA8775P | 0.497 ms | 0 - 21 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® QCS9075 | 0.394 ms | 0 - 2 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 0.548 ms | 0 - 29 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® SA7255P | 1.117 ms | 0 - 21 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® SA8295P | 0.677 ms | 0 - 17 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.198 ms | 0 - 20 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.194 ms | 0 - 24 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 0.17 ms | 0 - 0 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® X Elite | 0.234 ms | 0 - 0 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.138 ms | 0 - 36 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 0.702 ms | 2 - 4 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 0.461 ms | 0 - 20 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.168 ms | 0 - 1 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® SA8775P | 0.317 ms | 0 - 21 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 0.225 ms | 0 - 2 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 0.596 ms | 0 - 23 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.239 ms | 0 - 37 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® SA7255P | 0.461 ms | 0 - 20 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® SA8295P | 0.431 ms | 0 - 17 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.124 ms | 0 - 24 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.213 ms | 0 - 24 MB | NPU |
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.112 ms | 0 - 22 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.22 ms | 0 - 41 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 1.148 ms | 0 - 23 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 0.273 ms | 0 - 5 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® SA8775P | 0.494 ms | 0 - 24 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® QCS9075 | 0.391 ms | 0 - 12 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 0.478 ms | 0 - 44 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® SA7255P | 1.148 ms | 0 - 23 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® SA8295P | 0.672 ms | 0 - 19 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.201 ms | 0 - 26 MB | NPU |
| Facial-Landmark-Detection | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.186 ms | 0 - 24 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.14 ms | 0 - 36 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS6490 | 0.628 ms | 0 - 7 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 0.47 ms | 0 - 20 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.173 ms | 0 - 9 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® SA8775P | 0.329 ms | 0 - 21 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS9075 | 0.23 ms | 0 - 7 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCM6690 | 0.593 ms | 0 - 23 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.239 ms | 0 - 35 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® SA7255P | 0.47 ms | 0 - 20 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® SA8295P | 0.463 ms | 0 - 17 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.125 ms | 0 - 23 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.22 ms | 0 - 23 MB | NPU |
| Facial-Landmark-Detection | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.114 ms | 0 - 22 MB | NPU |
License
- The license for the original implementation of Facial-Landmark-Detection can be found here.
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.
