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  # MediaPipe-Face-Detection: Optimized for Mobile Deployment
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  ## Detect faces and locate facial features in real-time video and image streams
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  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.
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- This model is an implementation of MediaPipe-Face-Detection found [here]({source_repo}).
 
 
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  This repository provides scripts to run MediaPipe-Face-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/mediapipe_face).
 
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  # MediaPipe-Face-Detection: Optimized for Mobile Deployment
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  ## Detect faces and locate facial features in real-time video and image streams
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  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.
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+ This model is an implementation of Posenet-Mobilenet found [here](https://github.com/zmurez/MediaPipePyTorch/).
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  This repository provides scripts to run MediaPipe-Face-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/mediapipe_face).