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library_name: pytorch
license: other
tags:
- backbone
- android
pipeline_tag: keypoint-detection
---

# 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](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/facemap_3dmm) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) 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](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/facemap_3dmm/releases/v0.47.0/facemap_3dmm-onnx-float.zip)
| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/facemap_3dmm/releases/v0.47.0/facemap_3dmm-onnx-w8a8.zip)
| QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/facemap_3dmm/releases/v0.47.0/facemap_3dmm-qnn_dlc-float.zip)
| QNN_DLC | w8a8 | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/facemap_3dmm/releases/v0.47.0/facemap_3dmm-qnn_dlc-w8a8.zip)
| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/facemap_3dmm/releases/v0.47.0/facemap_3dmm-tflite-float.zip)
| TFLITE | w8a8 | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/facemap_3dmm/releases/v0.47.0/facemap_3dmm-tflite-w8a8.zip)
For more device-specific assets and performance metrics, visit **[Facial-Landmark-Detection on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/facemap_3dmm)**.
### Option 2: Export with Custom Configurations
Use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/facemap_3dmm) 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](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/facemap_3dmm) 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® X Elite | 0.394 ms | 10 - 10 MB | NPU
| Facial-Landmark-Detection | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.241 ms | 0 - 29 MB | NPU
| Facial-Landmark-Detection | ONNX | float | Qualcomm® QCS8550 (Proxy) | 0.32 ms | 0 - 32 MB | NPU
| Facial-Landmark-Detection | ONNX | float | Qualcomm® QCS9075 | 0.436 ms | 0 - 3 MB | NPU
| Facial-Landmark-Detection | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.225 ms | 0 - 24 MB | NPU
| Facial-Landmark-Detection | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.208 ms | 0 - 23 MB | NPU
| Facial-Landmark-Detection | ONNX | float | Snapdragon® X2 Elite | 0.168 ms | 10 - 10 MB | NPU
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® X Elite | 0.237 ms | 5 - 5 MB | NPU
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.139 ms | 0 - 38 MB | NPU
| Facial-Landmark-Detection | ONNX | w8a8 | Qualcomm® QCS6490 | 3.099 ms | 1 - 8 MB | CPU
| Facial-Landmark-Detection | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.173 ms | 0 - 8 MB | NPU
| Facial-Landmark-Detection | ONNX | w8a8 | Qualcomm® QCS9075 | 0.247 ms | 0 - 3 MB | NPU
| Facial-Landmark-Detection | ONNX | w8a8 | Qualcomm® QCM6690 | 1.684 ms | 0 - 6 MB | CPU
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.12 ms | 0 - 20 MB | NPU
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 1.271 ms | 0 - 7 MB | CPU
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.111 ms | 0 - 23 MB | NPU
| Facial-Landmark-Detection | ONNX | w8a8 | Snapdragon® X2 Elite | 0.077 ms | 5 - 5 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® X Elite | 0.374 ms | 0 - 0 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.223 ms | 0 - 30 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 1.123 ms | 0 - 21 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 0.294 ms | 0 - 2 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® SA8775P | 0.5 ms | 0 - 22 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® QCS9075 | 0.391 ms | 0 - 2 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 0.549 ms | 0 - 30 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® SA7255P | 1.123 ms | 0 - 21 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Qualcomm® SA8295P | 0.688 ms | 0 - 17 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.197 ms | 0 - 20 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.189 ms | 0 - 23 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | float | Snapdragon® X2 Elite | 0.246 ms | 0 - 0 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® X Elite | 0.237 ms | 0 - 0 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.14 ms | 0 - 36 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 0.708 ms | 0 - 2 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 0.453 ms | 0 - 20 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.163 ms | 0 - 1 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® SA8775P | 0.323 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 | 0.595 ms | 0 - 23 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.238 ms | 0 - 37 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® SA7255P | 0.453 ms | 0 - 20 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Qualcomm® SA8295P | 0.457 ms | 0 - 17 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.113 ms | 0 - 19 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.214 ms | 2 - 25 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.11 ms | 0 - 22 MB | NPU
| Facial-Landmark-Detection | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 0.166 ms | 0 - 0 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.224 ms | 0 - 41 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 1.156 ms | 0 - 22 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 0.282 ms | 0 - 2 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® SA8775P | 0.498 ms | 0 - 24 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® QCS9075 | 0.382 ms | 0 - 12 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 0.474 ms | 0 - 41 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® SA7255P | 1.156 ms | 0 - 22 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Qualcomm® SA8295P | 0.682 ms | 0 - 18 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.195 ms | 0 - 21 MB | NPU
| Facial-Landmark-Detection | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.192 ms | 0 - 24 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.136 ms | 0 - 36 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS6490 | 0.59 ms | 0 - 7 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 0.483 ms | 0 - 20 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.169 ms | 0 - 1 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® SA8775P | 0.335 ms | 0 - 21 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS9075 | 0.227 ms | 0 - 7 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCM6690 | 0.599 ms | 0 - 22 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.239 ms | 0 - 37 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® SA7255P | 0.483 ms | 0 - 20 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Qualcomm® SA8295P | 0.485 ms | 0 - 17 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.123 ms | 0 - 18 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.219 ms | 0 - 23 MB | NPU
| Facial-Landmark-Detection | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.118 ms | 0 - 22 MB | NPU
## License
* The license for the original implementation of Facial-Landmark-Detection can be found
[here](https://github.com/quic/ai-hub-models/blob/main/LICENSE).
## Community
* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).
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