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README.md
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# MediaPipe-Face-Detection-Quantized: 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
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This repository provides scripts to run MediaPipe-Face-Detection-Quantized 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_quantized).
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# MediaPipe-Face-Detection-Quantized: 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-Quantized 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_quantized).
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