Import cv2 import mediapipe as mp mp_face_detection = mp. Please first follow general instructions to install MediaPipe Python package, then learn more in the companion Python Colab and the usage example below. Each key point is composed of x and y, which are normalized to by the image width and height respectively. The bounding box is composed of xmin and width (both normalized to by the image width) and ymin and height (both normalized to by the image height). detectionsĬollection of detected faces, where each face is represented as a detection proto message that contains a bounding box and 6 key points (right eye, left eye, nose tip, mouth center, right ear tragion, and left ear tragion). Naming style may differ slightly across platforms/languages. Minimum confidence value ( ) from the face detection model for the detection to be considered successful. Please refer to the model cards for details.

For the full-range option, a sparse model is used for its improved inference speed. Use 0 to select a short-range model that works best for faces within 2 meters from the camera, and 1 for a full-range model best for faces within 5 meters. Naming style and availability may differ slightly across platforms/languages. For more information about BlazeFace, please see the Resources section. BlazeFace uses a lightweight feature extraction network inspired by, but distinct from MobileNetV1/V2, a GPU-friendly anchor scheme modified from Single Shot MultiBox Detector (SSD), and an improved tie resolution strategy alternative to non-maximum suppression. The detector’s super-realtime performance enables it to be applied to any live viewfinder experience that requires an accurate facial region of interest as an input for other task-specific models, such as 3D facial keypoint or geometry estimation (e.g., MediaPipe Face Mesh), facial features or expression classification, and face region segmentation. It is based on BlazeFace, a lightweight and well-performing face detector tailored for mobile GPU inference. MediaPipe Face Detection is an ultrafast face detection solution that comes with 6 landmarks and multi-face support. MediaPipe Face Detection Table of contents

This site uses Just the Docs, a documentation theme for Jekyll.

YouTube-8M Feature Extraction and Model Inference.

AutoFlip (Saliency-aware Video Cropping).

KNIFT (Template-based Feature Matching).

Face visualizer 3d