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--- |
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library_name: pytorch |
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license: other |
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tags: |
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- backbone |
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- android |
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pipeline_tag: keypoint-detection |
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--- |
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# Facial-Landmark-Detection: Optimized for Mobile Deployment |
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## Real-time 3D facial landmark detection optimized for mobile and edge |
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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. |
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This repository provides scripts to run Facial-Landmark-Detection on Qualcomm® devices. |
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More details on model performance across various devices, can be found |
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[here](https://aihub.qualcomm.com/models/facemap_3dmm). |
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### Model Details |
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- **Model Type:** Model_use_case.pose_estimation |
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- **Model Stats:** |
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- Input resolution: 128x128 |
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- Number of parameters: 5.42M |
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- Model size (float): 20.7 MB |
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- Model size (w8a8): 5.27 MB |
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| Model | Precision | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit | Target Model |
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|---|---|---|---|---|---|---|---|---| |
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| Facial-Landmark-Detection | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 1.131 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 1.137 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 0.481 ms | 0 - 146 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 0.551 ms | 0 - 130 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 0.281 ms | 0 - 10 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 0.298 ms | 0 - 3 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | ONNX | 0.514 ms | 0 - 15 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.onnx.zip) | |
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| Facial-Landmark-Detection | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 0.503 ms | 0 - 116 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 0.515 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 1.131 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 1.137 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 0.641 ms | 0 - 121 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 0.64 ms | 0 - 120 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | SA8775P ADP | Qualcomm® SA8775P | TFLITE | 0.503 ms | 0 - 116 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 0.515 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 0.225 ms | 0 - 144 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 0.236 ms | 0 - 129 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 0.332 ms | 0 - 103 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.onnx.zip) | |
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| Facial-Landmark-Detection | float | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | TFLITE | 0.19 ms | 0 - 120 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | QNN_DLC | 0.198 ms | 0 - 118 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | ONNX | 0.318 ms | 0 - 90 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.onnx.zip) | |
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| Facial-Landmark-Detection | float | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen 5 Mobile | TFLITE | 0.189 ms | 0 - 119 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | |
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| Facial-Landmark-Detection | float | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen 5 Mobile | QNN_DLC | 0.196 ms | 0 - 118 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen 5 Mobile | ONNX | 0.316 ms | 0 - 91 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.onnx.zip) | |
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| Facial-Landmark-Detection | float | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 0.367 ms | 0 - 0 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | |
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| Facial-Landmark-Detection | float | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 0.394 ms | 10 - 10 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.onnx.zip) | |
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| Facial-Landmark-Detection | w8a8 | Dragonwing Q-6690 MTP | Qualcomm® QCM6690 | TFLITE | 0.604 ms | 0 - 123 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | Dragonwing Q-6690 MTP | Qualcomm® QCM6690 | QNN_DLC | 0.597 ms | 0 - 124 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | Dragonwing Q-6690 MTP | Qualcomm® QCM6690 | ONNX | 1.664 ms | 0 - 13 MB | CPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | |
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| Facial-Landmark-Detection | w8a8 | Dragonwing RB3 Gen 2 Vision Kit | Qualcomm® QCS6490 | TFLITE | 0.604 ms | 0 - 7 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | Dragonwing RB3 Gen 2 Vision Kit | Qualcomm® QCS6490 | QNN_DLC | 0.693 ms | 0 - 2 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | Dragonwing RB3 Gen 2 Vision Kit | Qualcomm® QCS6490 | ONNX | 2.776 ms | 2 - 12 MB | CPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | |
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| Facial-Landmark-Detection | w8a8 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 0.46 ms | 0 - 114 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 0.43 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 0.27 ms | 0 - 138 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 0.247 ms | 0 - 137 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 0.169 ms | 0 - 3 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 0.17 ms | 0 - 2 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | ONNX | 0.365 ms | 0 - 9 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | |
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| Facial-Landmark-Detection | w8a8 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 0.331 ms | 0 - 114 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 0.311 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 0.46 ms | 0 - 114 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 0.43 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 0.441 ms | 0 - 120 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 0.443 ms | 0 - 121 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | SA8775P ADP | Qualcomm® SA8775P | TFLITE | 0.331 ms | 0 - 114 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 0.311 ms | 0 - 115 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 0.14 ms | 0 - 139 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 0.14 ms | 0 - 139 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 0.227 ms | 0 - 114 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | |
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| Facial-Landmark-Detection | w8a8 | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | TFLITE | 0.123 ms | 0 - 118 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | QNN_DLC | 0.118 ms | 0 - 119 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | Samsung Galaxy S25 | Snapdragon® 8 Elite For Galaxy Mobile | ONNX | 0.209 ms | 0 - 91 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | |
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| Facial-Landmark-Detection | w8a8 | Snapdragon 7 Gen 4 QRD | Snapdragon® 7 Gen 4 Mobile | TFLITE | 0.224 ms | 0 - 123 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | Snapdragon 7 Gen 4 QRD | Snapdragon® 7 Gen 4 Mobile | QNN_DLC | 0.22 ms | 0 - 124 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | Snapdragon 7 Gen 4 QRD | Snapdragon® 7 Gen 4 Mobile | ONNX | 1.553 ms | 2 - 18 MB | CPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | |
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| Facial-Landmark-Detection | w8a8 | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen 5 Mobile | TFLITE | 0.126 ms | 0 - 116 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | |
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| Facial-Landmark-Detection | w8a8 | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen 5 Mobile | QNN_DLC | 0.119 ms | 0 - 117 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | Snapdragon 8 Elite Gen 5 QRD | Snapdragon® 8 Elite Gen 5 Mobile | ONNX | 0.27 ms | 0 - 93 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | |
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| Facial-Landmark-Detection | w8a8 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 0.236 ms | 0 - 0 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | |
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| Facial-Landmark-Detection | w8a8 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 0.232 ms | 5 - 5 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | |
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## Installation |
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Install the package via pip: |
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```bash |
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# NOTE: 3.10 <= PYTHON_VERSION < 3.14 is supported. |
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pip install "qai-hub-models[facemap-3dmm]" |
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``` |
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## Configure Qualcomm® AI Hub Workbench to run this model on a cloud-hosted device |
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Sign-in to [Qualcomm® AI Hub Workbench](https://workbench.aihub.qualcomm.com/) with your |
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Qualcomm® ID. Once signed in navigate to `Account -> Settings -> API Token`. |
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With this API token, you can configure your client to run models on the cloud |
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hosted devices. |
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```bash |
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qai-hub configure --api_token API_TOKEN |
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``` |
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Navigate to [docs](https://workbench.aihub.qualcomm.com/docs/) for more information. |
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## Demo off target |
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The package contains a simple end-to-end demo that downloads pre-trained |
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weights and runs this model on a sample input. |
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```bash |
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python -m qai_hub_models.models.facemap_3dmm.demo |
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``` |
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The above demo runs a reference implementation of pre-processing, model |
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inference, and post processing. |
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**NOTE**: If you want running in a Jupyter Notebook or Google Colab like |
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environment, please add the following to your cell (instead of the above). |
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``` |
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%run -m qai_hub_models.models.facemap_3dmm.demo |
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``` |
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### Run model on a cloud-hosted device |
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In addition to the demo, you can also run the model on a cloud-hosted Qualcomm® |
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device. This script does the following: |
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* Performance check on-device on a cloud-hosted device |
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* Downloads compiled assets that can be deployed on-device for Android. |
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* Accuracy check between PyTorch and on-device outputs. |
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```bash |
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python -m qai_hub_models.models.facemap_3dmm.export |
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``` |
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## How does this work? |
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This [export script](https://aihub.qualcomm.com/models/facemap_3dmm/qai_hub_models/models/Facial-Landmark-Detection/export.py) |
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leverages [Qualcomm® AI Hub](https://aihub.qualcomm.com/) to optimize, validate, and deploy this model |
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on-device. Lets go through each step below in detail: |
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Step 1: **Compile model for on-device deployment** |
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To compile a PyTorch model for on-device deployment, we first trace the model |
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in memory using the `jit.trace` and then call the `submit_compile_job` API. |
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```python |
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import torch |
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import qai_hub as hub |
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from qai_hub_models.models.facemap_3dmm import Model |
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# Load the model |
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torch_model = Model.from_pretrained() |
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# Device |
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device = hub.Device("Samsung Galaxy S25") |
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# Trace model |
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input_shape = torch_model.get_input_spec() |
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sample_inputs = torch_model.sample_inputs() |
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pt_model = torch.jit.trace(torch_model, [torch.tensor(data[0]) for _, data in sample_inputs.items()]) |
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# Compile model on a specific device |
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compile_job = hub.submit_compile_job( |
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model=pt_model, |
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device=device, |
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input_specs=torch_model.get_input_spec(), |
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) |
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# Get target model to run on-device |
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target_model = compile_job.get_target_model() |
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``` |
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Step 2: **Performance profiling on cloud-hosted device** |
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After compiling models from step 1. Models can be profiled model on-device using the |
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`target_model`. Note that this scripts runs the model on a device automatically |
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provisioned in the cloud. Once the job is submitted, you can navigate to a |
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provided job URL to view a variety of on-device performance metrics. |
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```python |
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profile_job = hub.submit_profile_job( |
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model=target_model, |
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device=device, |
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) |
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``` |
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Step 3: **Verify on-device accuracy** |
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To verify the accuracy of the model on-device, you can run on-device inference |
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on sample input data on the same cloud hosted device. |
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```python |
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input_data = torch_model.sample_inputs() |
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inference_job = hub.submit_inference_job( |
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model=target_model, |
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device=device, |
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inputs=input_data, |
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) |
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on_device_output = inference_job.download_output_data() |
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``` |
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With the output of the model, you can compute like PSNR, relative errors or |
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spot check the output with expected output. |
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**Note**: This on-device profiling and inference requires access to Qualcomm® |
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AI Hub Workbench. [Sign up for access](https://myaccount.qualcomm.com/signup). |
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## Run demo on a cloud-hosted device |
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You can also run the demo on-device. |
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```bash |
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python -m qai_hub_models.models.facemap_3dmm.demo --eval-mode on-device |
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``` |
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**NOTE**: If you want running in a Jupyter Notebook or Google Colab like |
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environment, please add the following to your cell (instead of the above). |
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``` |
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%run -m qai_hub_models.models.facemap_3dmm.demo -- --eval-mode on-device |
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``` |
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## Deploying compiled model to Android |
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The models can be deployed using multiple runtimes: |
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- TensorFlow Lite (`.tflite` export): [This |
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tutorial](https://www.tensorflow.org/lite/android/quickstart) provides a |
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guide to deploy the .tflite model in an Android application. |
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- QNN (`.so` export ): This [sample |
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app](https://docs.qualcomm.com/bundle/publicresource/topics/80-63442-50/sample_app.html) |
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provides instructions on how to use the `.so` shared library in an Android application. |
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## View on Qualcomm® AI Hub |
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Get more details on Facial-Landmark-Detection's performance across various devices [here](https://aihub.qualcomm.com/models/facemap_3dmm). |
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Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/) |
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## License |
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* The license for the original implementation of Facial-Landmark-Detection can be found |
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[here](https://github.com/quic/ai-hub-models/blob/main/LICENSE). |
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## Community |
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* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI. |
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* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com). |
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