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MediaPipe-Face-Detection-Quantized

Object Detection
PyTorch
LiteRT
ONNX
real_time
quantized
android
Model card Files Community

MediaPipe-Face-Detection-Quantized: Optimized for Mobile Deployment

Detect faces and locate facial features in real-time video and image streams

Designed for sub-millisecond processing, this model predicts bounding boxes and pose skeletons (left eye, right eye, nose tip, mouth, left eye tragion, and right eye tragion) of faces in an image.

This model is an implementation of MediaPipe-Face-Detection-Quantized found here.

This repository provides scripts to run MediaPipe-Face-Detection-Quantized on Qualcomm® devices. More details on model performance across various devices, can be found here.

Model Details

  • Model Type: Object detection
  • Model Stats:
    • Input resolution: 256x256
    • Number of output classes: 6
    • Number of parameters (MediaPipeFaceDetector): 135K
    • Model size (MediaPipeFaceDetector): 255 KB
    • Number of parameters (MediaPipeFaceLandmarkDetector): 603K
    • Model size (MediaPipeFaceLandmarkDetector): 746 KB
Model Device Chipset Target Runtime Inference Time (ms) Peak Memory Range (MB) Precision Primary Compute Unit Target Model
FaceDetectorQuantizable Samsung Galaxy S23 Snapdragon® 8 Gen 2 TFLITE 0.262 ms 0 - 11 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable Samsung Galaxy S23 Snapdragon® 8 Gen 2 QNN 0.243 ms 0 - 12 MB INT8 NPU MediaPipe-Face-Detection-Quantized.so
FaceDetectorQuantizable Samsung Galaxy S23 Snapdragon® 8 Gen 2 ONNX 0.48 ms 2 - 13 MB INT8 NPU MediaPipe-Face-Detection-Quantized.onnx
FaceDetectorQuantizable Samsung Galaxy S24 Snapdragon® 8 Gen 3 TFLITE 0.18 ms 0 - 24 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable Samsung Galaxy S24 Snapdragon® 8 Gen 3 QNN 0.165 ms 0 - 28 MB INT8 NPU MediaPipe-Face-Detection-Quantized.so
FaceDetectorQuantizable Samsung Galaxy S24 Snapdragon® 8 Gen 3 ONNX 0.309 ms 0 - 24 MB INT8 NPU MediaPipe-Face-Detection-Quantized.onnx
FaceDetectorQuantizable Snapdragon 8 Elite QRD Snapdragon® 8 Elite TFLITE 0.157 ms 0 - 20 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable Snapdragon 8 Elite QRD Snapdragon® 8 Elite QNN 0.131 ms 0 - 20 MB INT8 NPU Use Export Script
FaceDetectorQuantizable Snapdragon 8 Elite QRD Snapdragon® 8 Elite ONNX 0.282 ms 0 - 20 MB INT8 NPU MediaPipe-Face-Detection-Quantized.onnx
FaceDetectorQuantizable SA7255P ADP SA7255P TFLITE 2.023 ms 0 - 17 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable SA7255P ADP SA7255P QNN 1.856 ms 0 - 10 MB INT8 NPU Use Export Script
FaceDetectorQuantizable SA8255 (Proxy) SA8255P Proxy TFLITE 0.27 ms 0 - 11 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable SA8255 (Proxy) SA8255P Proxy QNN 0.241 ms 0 - 3 MB INT8 NPU Use Export Script
FaceDetectorQuantizable SA8295P ADP SA8295P TFLITE 0.669 ms 0 - 21 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable SA8295P ADP SA8295P QNN 0.576 ms 0 - 18 MB INT8 NPU Use Export Script
FaceDetectorQuantizable SA8650 (Proxy) SA8650P Proxy TFLITE 0.264 ms 0 - 11 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable SA8650 (Proxy) SA8650P Proxy QNN 0.239 ms 0 - 2 MB INT8 NPU Use Export Script
FaceDetectorQuantizable SA8775P ADP SA8775P TFLITE 0.55 ms 0 - 17 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable SA8775P ADP SA8775P QNN 0.51 ms 0 - 10 MB INT8 NPU Use Export Script
FaceDetectorQuantizable RB3 Gen 2 (Proxy) QCS6490 Proxy TFLITE 0.697 ms 0 - 22 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable RB3 Gen 2 (Proxy) QCS6490 Proxy QNN 0.64 ms 0 - 13 MB INT8 NPU Use Export Script
FaceDetectorQuantizable RB5 (Proxy) QCS8250 Proxy TFLITE 4.791 ms 0 - 2 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable QCS8275 (Proxy) QCS8275 Proxy TFLITE 2.023 ms 0 - 17 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable QCS8275 (Proxy) QCS8275 Proxy QNN 1.856 ms 0 - 10 MB INT8 NPU Use Export Script
FaceDetectorQuantizable QCS8550 (Proxy) QCS8550 Proxy TFLITE 0.266 ms 0 - 11 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable QCS8550 (Proxy) QCS8550 Proxy QNN 0.237 ms 0 - 3 MB INT8 NPU Use Export Script
FaceDetectorQuantizable QCS9075 (Proxy) QCS9075 Proxy TFLITE 0.55 ms 0 - 17 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable QCS9075 (Proxy) QCS9075 Proxy QNN 0.51 ms 0 - 10 MB INT8 NPU Use Export Script
FaceDetectorQuantizable QCS8450 (Proxy) QCS8450 Proxy TFLITE 0.374 ms 0 - 28 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceDetectorQuantizable QCS8450 (Proxy) QCS8450 Proxy QNN 0.362 ms 0 - 25 MB INT8 NPU Use Export Script
FaceDetectorQuantizable Snapdragon X Elite CRD Snapdragon® X Elite QNN 0.323 ms 0 - 0 MB INT8 NPU Use Export Script
FaceDetectorQuantizable Snapdragon X Elite CRD Snapdragon® X Elite ONNX 0.418 ms 1 - 1 MB INT8 NPU MediaPipe-Face-Detection-Quantized.onnx
FaceLandmarkDetectorQuantizable Samsung Galaxy S23 Snapdragon® 8 Gen 2 TFLITE 0.182 ms 0 - 11 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable Samsung Galaxy S23 Snapdragon® 8 Gen 2 QNN 0.153 ms 0 - 11 MB INT8 NPU MediaPipe-Face-Detection-Quantized.so
FaceLandmarkDetectorQuantizable Samsung Galaxy S23 Snapdragon® 8 Gen 2 ONNX 0.47 ms 0 - 9 MB INT8 NPU MediaPipe-Face-Detection-Quantized.onnx
FaceLandmarkDetectorQuantizable Samsung Galaxy S24 Snapdragon® 8 Gen 3 TFLITE 0.139 ms 0 - 22 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable Samsung Galaxy S24 Snapdragon® 8 Gen 3 QNN 0.118 ms 0 - 19 MB INT8 NPU MediaPipe-Face-Detection-Quantized.so
FaceLandmarkDetectorQuantizable Samsung Galaxy S24 Snapdragon® 8 Gen 3 ONNX 0.325 ms 0 - 26 MB INT8 NPU MediaPipe-Face-Detection-Quantized.onnx
FaceLandmarkDetectorQuantizable Snapdragon 8 Elite QRD Snapdragon® 8 Elite TFLITE 0.134 ms 0 - 19 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable Snapdragon 8 Elite QRD Snapdragon® 8 Elite QNN 0.115 ms 0 - 19 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable Snapdragon 8 Elite QRD Snapdragon® 8 Elite ONNX 0.347 ms 0 - 17 MB INT8 NPU MediaPipe-Face-Detection-Quantized.onnx
FaceLandmarkDetectorQuantizable SA7255P ADP SA7255P TFLITE 0.869 ms 0 - 12 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable SA7255P ADP SA7255P QNN 0.798 ms 0 - 10 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable SA8255 (Proxy) SA8255P Proxy TFLITE 0.181 ms 0 - 5 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable SA8255 (Proxy) SA8255P Proxy QNN 0.159 ms 0 - 2 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable SA8295P ADP SA8295P TFLITE 0.502 ms 0 - 17 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable SA8295P ADP SA8295P QNN 0.464 ms 0 - 18 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable SA8650 (Proxy) SA8650P Proxy TFLITE 0.185 ms 0 - 10 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable SA8650 (Proxy) SA8650P Proxy QNN 0.15 ms 0 - 2 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable SA8775P ADP SA8775P TFLITE 0.429 ms 0 - 12 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable SA8775P ADP SA8775P QNN 0.391 ms 0 - 10 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable RB3 Gen 2 (Proxy) QCS6490 Proxy TFLITE 0.403 ms 0 - 21 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable RB3 Gen 2 (Proxy) QCS6490 Proxy QNN 0.392 ms 0 - 15 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable RB5 (Proxy) QCS8250 Proxy TFLITE 2.793 ms 0 - 3 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable QCS8275 (Proxy) QCS8275 Proxy TFLITE 0.869 ms 0 - 12 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable QCS8275 (Proxy) QCS8275 Proxy QNN 0.798 ms 0 - 10 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable QCS8550 (Proxy) QCS8550 Proxy TFLITE 0.174 ms 0 - 10 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable QCS8550 (Proxy) QCS8550 Proxy QNN 0.154 ms 0 - 2 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable QCS9075 (Proxy) QCS9075 Proxy TFLITE 0.429 ms 0 - 12 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable QCS9075 (Proxy) QCS9075 Proxy QNN 0.391 ms 0 - 10 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable QCS8450 (Proxy) QCS8450 Proxy TFLITE 0.281 ms 0 - 23 MB INT8 NPU MediaPipe-Face-Detection-Quantized.tflite
FaceLandmarkDetectorQuantizable QCS8450 (Proxy) QCS8450 Proxy QNN 0.256 ms 0 - 24 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable Snapdragon X Elite CRD Snapdragon® X Elite QNN 0.228 ms 1 - 1 MB INT8 NPU Use Export Script
FaceLandmarkDetectorQuantizable Snapdragon X Elite CRD Snapdragon® X Elite ONNX 0.479 ms 0 - 0 MB INT8 NPU MediaPipe-Face-Detection-Quantized.onnx

Installation

Install the package via pip:

pip install "qai-hub-models[mediapipe-face-quantized]"

Configure Qualcomm® AI Hub to run this model on a cloud-hosted device

Sign-in to Qualcomm® AI Hub 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.

qai-hub configure --api_token API_TOKEN

Navigate to 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.

python -m qai_hub_models.models.mediapipe_face_quantized.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.mediapipe_face_quantized.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.
python -m qai_hub_models.models.mediapipe_face_quantized.export

Profiling Results
------------------------------------------------------------
FaceDetectorQuantizable
Device                          : Samsung Galaxy S23 (13)
Runtime                         : TFLITE                 
Estimated inference time (ms)   : 0.3                    
Estimated peak memory usage (MB): [0, 11]                
Total # Ops                     : 121                    
Compute Unit(s)                 : NPU (121 ops)          

------------------------------------------------------------
FaceLandmarkDetectorQuantizable
Device                          : Samsung Galaxy S23 (13)
Runtime                         : TFLITE                 
Estimated inference time (ms)   : 0.2                    
Estimated peak memory usage (MB): [0, 11]                
Total # Ops                     : 116                    
Compute Unit(s)                 : NPU (116 ops)

Deploying compiled model to Android

The models can be deployed using multiple runtimes:

  • TensorFlow Lite (.tflite export): This tutorial provides a guide to deploy the .tflite model in an Android application.

  • QNN (.so export ): This sample app provides instructions on how to use the .so shared library in an Android application.

View on Qualcomm® AI Hub

Get more details on MediaPipe-Face-Detection-Quantized's performance across various devices here. Explore all available models on Qualcomm® AI Hub

License

  • The license for the original implementation of MediaPipe-Face-Detection-Quantized can be found here.
  • The license for the compiled assets for on-device deployment can be found here

References

Community

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