--- library_name: pytorch license: other tags: - backbone - android pipeline_tag: keypoint-detection --- ![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/facemap_3dmm/web-assets/model_demo.png) # Facial-Landmark-Detection: Optimized for Mobile Deployment ## Real-time 3D facial landmark detection optimized for mobile and edge 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 provides scripts to run Facial-Landmark-Detection on Qualcomm® devices. More details on model performance across various devices, can be found [here](https://aihub.qualcomm.com/models/facemap_3dmm). ### 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 | Model | Precision | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit | Target Model |---|---|---|---|---|---|---|---|---| | Facial-Landmark-Detection | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 1.163 ms | 0 - 17 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 1.144 ms | 0 - 16 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 0.384 ms | 0 - 37 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 0.544 ms | 0 - 25 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 0.281 ms | 0 - 100 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 0.279 ms | 0 - 42 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 0.497 ms | 0 - 16 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 1.163 ms | 0 - 17 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 1.144 ms | 0 - 16 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | TFLITE | 0.281 ms | 0 - 100 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | QNN_DLC | 0.288 ms | 0 - 41 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 0.654 ms | 0 - 24 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 0.649 ms | 0 - 21 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | TFLITE | 0.286 ms | 0 - 99 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | QNN_DLC | 0.289 ms | 0 - 46 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 0.497 ms | 0 - 16 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | TFLITE | 0.285 ms | 0 - 101 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN_DLC | 0.292 ms | 0 - 38 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 0.406 ms | 0 - 41 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.onnx.zip) | | Facial-Landmark-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 0.221 ms | 0 - 35 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 0.233 ms | 0 - 23 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 0.327 ms | 0 - 20 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.onnx.zip) | | Facial-Landmark-Detection | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | TFLITE | 0.228 ms | 0 - 18 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.tflite) | | Facial-Landmark-Detection | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN_DLC | 0.221 ms | 0 - 21 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX | 0.32 ms | 0 - 21 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.onnx.zip) | | Facial-Landmark-Detection | float | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 0.359 ms | 35 - 35 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.dlc) | | Facial-Landmark-Detection | float | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 0.406 ms | 12 - 12 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection.onnx.zip) | | Facial-Landmark-Detection | w8a8 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | TFLITE | 0.456 ms | 0 - 15 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | QCS8275 (Proxy) | Qualcomm® QCS8275 (Proxy) | QNN_DLC | 0.423 ms | 0 - 16 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | TFLITE | 0.22 ms | 0 - 33 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | QCS8450 (Proxy) | Qualcomm® QCS8450 (Proxy) | QNN_DLC | 0.234 ms | 0 - 36 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | TFLITE | 0.172 ms | 0 - 43 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | QCS8550 (Proxy) | Qualcomm® QCS8550 (Proxy) | QNN_DLC | 0.167 ms | 0 - 43 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | TFLITE | 0.327 ms | 0 - 15 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | QCS9075 (Proxy) | Qualcomm® QCS9075 (Proxy) | QNN_DLC | 0.312 ms | 0 - 16 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | RB3 Gen 2 (Proxy) | Qualcomm® QCS6490 (Proxy) | TFLITE | 0.52 ms | 0 - 25 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | RB3 Gen 2 (Proxy) | Qualcomm® QCS6490 (Proxy) | QNN_DLC | 0.581 ms | 0 - 25 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | RB5 (Proxy) | Qualcomm® QCS8250 (Proxy) | TFLITE | 2.073 ms | 0 - 3 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | SA7255P ADP | Qualcomm® SA7255P | TFLITE | 0.456 ms | 0 - 15 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | SA7255P ADP | Qualcomm® SA7255P | QNN_DLC | 0.423 ms | 0 - 16 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | TFLITE | 0.179 ms | 0 - 44 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | SA8255 (Proxy) | Qualcomm® SA8255P (Proxy) | QNN_DLC | 0.157 ms | 0 - 44 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | SA8295P ADP | Qualcomm® SA8295P | TFLITE | 0.464 ms | 0 - 21 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | SA8295P ADP | Qualcomm® SA8295P | QNN_DLC | 0.437 ms | 0 - 21 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | TFLITE | 0.176 ms | 0 - 41 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | SA8650 (Proxy) | Qualcomm® SA8650P (Proxy) | QNN_DLC | 0.168 ms | 0 - 42 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | SA8775P ADP | Qualcomm® SA8775P | TFLITE | 0.327 ms | 0 - 15 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | SA8775P ADP | Qualcomm® SA8775P | QNN_DLC | 0.312 ms | 0 - 16 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | TFLITE | 0.17 ms | 0 - 3 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | QNN_DLC | 0.164 ms | 0 - 43 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 Mobile | ONNX | 7.903 ms | 9 - 100 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | | Facial-Landmark-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | TFLITE | 0.134 ms | 0 - 33 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_DLC | 0.137 ms | 0 - 35 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | ONNX | 6.765 ms | 10 - 272 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | | Facial-Landmark-Detection | w8a8 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | TFLITE | 0.127 ms | 0 - 21 MB | NPU | [Facial-Landmark-Detection.tflite](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.tflite) | | Facial-Landmark-Detection | w8a8 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN_DLC | 0.115 ms | 0 - 26 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | ONNX | 6.512 ms | 3 - 334 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | | Facial-Landmark-Detection | w8a8 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_DLC | 0.24 ms | 32 - 32 MB | NPU | [Facial-Landmark-Detection.dlc](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.dlc) | | Facial-Landmark-Detection | w8a8 | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 9.953 ms | 12 - 12 MB | NPU | [Facial-Landmark-Detection.onnx.zip](https://huggingface.co/qualcomm/Facial-Landmark-Detection/blob/main/Facial-Landmark-Detection_w8a8.onnx.zip) | ## Installation Install the package via pip: ```bash pip install "qai-hub-models[facemap-3dmm]" ``` ## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your Qualcomm® ID. Once signed in navigate to `Account -> Settings -> API Token`. With this API token, you can configure your client to run models on the cloud hosted devices. ```bash qai-hub configure --api_token API_TOKEN ``` Navigate to [docs](https://app.aihub.qualcomm.com/docs/) for more information. ## Demo off target The package contains a simple end-to-end demo that downloads pre-trained weights and runs this model on a sample input. ```bash python -m qai_hub_models.models.facemap_3dmm.demo ``` The above demo runs a reference implementation of pre-processing, model inference, and post processing. **NOTE**: If you want running in a Jupyter Notebook or Google Colab like environment, please add the following to your cell (instead of the above). ``` %run -m qai_hub_models.models.facemap_3dmm.demo ``` ### Run model on a cloud-hosted device In addition to the demo, you can also run the model on a cloud-hosted Qualcomm® device. This script does the following: * Performance check on-device on a cloud-hosted device * Downloads compiled assets that can be deployed on-device for Android. * Accuracy check between PyTorch and on-device outputs. ```bash python -m qai_hub_models.models.facemap_3dmm.export ``` ## How does this work? This [export script](https://aihub.qualcomm.com/models/facemap_3dmm/qai_hub_models/models/Facial-Landmark-Detection/export.py) leverages [Qualcomm® AI Hub](https://aihub.qualcomm.com/) to optimize, validate, and deploy this model on-device. Lets go through each step below in detail: Step 1: **Compile model for on-device deployment** To compile a PyTorch model for on-device deployment, we first trace the model in memory using the `jit.trace` and then call the `submit_compile_job` API. ```python import torch import qai_hub as hub from qai_hub_models.models.facemap_3dmm import Model # Load the model torch_model = Model.from_pretrained() # Device device = hub.Device("Samsung Galaxy S24") # Trace model input_shape = torch_model.get_input_spec() sample_inputs = torch_model.sample_inputs() pt_model = torch.jit.trace(torch_model, [torch.tensor(data[0]) for _, data in sample_inputs.items()]) # Compile model on a specific device compile_job = hub.submit_compile_job( model=pt_model, device=device, input_specs=torch_model.get_input_spec(), ) # Get target model to run on-device target_model = compile_job.get_target_model() ``` Step 2: **Performance profiling on cloud-hosted device** After compiling models from step 1. Models can be profiled model on-device using the `target_model`. Note that this scripts runs the model on a device automatically provisioned in the cloud. Once the job is submitted, you can navigate to a provided job URL to view a variety of on-device performance metrics. ```python profile_job = hub.submit_profile_job( model=target_model, device=device, ) ``` Step 3: **Verify on-device accuracy** To verify the accuracy of the model on-device, you can run on-device inference on sample input data on the same cloud hosted device. ```python input_data = torch_model.sample_inputs() inference_job = hub.submit_inference_job( model=target_model, device=device, inputs=input_data, ) on_device_output = inference_job.download_output_data() ``` With the output of the model, you can compute like PSNR, relative errors or spot check the output with expected output. **Note**: This on-device profiling and inference requires access to Qualcomm® AI Hub. [Sign up for access](https://myaccount.qualcomm.com/signup). ## Run demo on a cloud-hosted device You can also run the demo on-device. ```bash python -m qai_hub_models.models.facemap_3dmm.demo --eval-mode on-device ``` **NOTE**: If you want running in a Jupyter Notebook or Google Colab like environment, please add the following to your cell (instead of the above). ``` %run -m qai_hub_models.models.facemap_3dmm.demo -- --eval-mode on-device ``` ## Deploying compiled model to Android The models can be deployed using multiple runtimes: - TensorFlow Lite (`.tflite` export): [This tutorial](https://www.tensorflow.org/lite/android/quickstart) provides a guide to deploy the .tflite model in an Android application. - QNN (`.so` export ): This [sample app](https://docs.qualcomm.com/bundle/publicresource/topics/80-63442-50/sample_app.html) provides instructions on how to use the `.so` shared library in an Android application. ## View on Qualcomm® AI Hub Get more details on Facial-Landmark-Detection's performance across various devices [here](https://aihub.qualcomm.com/models/facemap_3dmm). Explore all available models on [Qualcomm® AI Hub](https://aihub.qualcomm.com/) ## 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). * The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf) ## 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).