Face descriptor with 128 entries or array thereof in case of batch input.
Detects the 68 point face landmark positions of the face shown in an image.
68 point face landmarks or array thereof in case of batch input.
Detects the 68 point face landmark positions of the face shown in an image using a tinier version of the 68 point face landmark model, which is slightly faster at inference, but also slightly less accurate.
68 point face landmarks or array thereof in case of batch input.
Extracts the tensors of the image regions containing the detected faces. Useful if you want to compute the face descriptors for the face images. Using this method is faster then extracting a canvas for each face and converting them to tensors individually.
The image tensor that face detection has been performed on.
The face detection results or face bounding boxes for that image.
Tensors of the corresponding image region for each detected face.
Extracts the image regions containing the detected faces.
The image that face detection has been performed on.
The face detection results or face bounding boxes for that image.
The Canvases of the corresponding image region for each detected face.
Attempts to detect all faces in an image and the 5 point face landmarks of each detected face using the MTCNN Network.
The input image.
(optional, default: see MtcnnOptions constructor for default parameters).
Bounding box of each face with score and 5 point face landmarks.
Pads the smaller dimension of an image tensor with zeros, such that width === height.
The image tensor.
(optional, default: false) If true, add an equal amount of padding on both sides of the minor dimension oof the image.
The padded tensor with width === height.
Recognizes the facial expressions of a face and returns the likelyhood of each facial expression.
An array of facial expressions with corresponding probabilities or array thereof in case of batch input.
Attempts to detect all faces in an image using SSD Mobilenetv1 Network.
The input image.
(optional, default: see SsdMobilenetv1Options constructor for default parameters).
Bounding box of each face with score.
Attempts to detect all faces in an image using the Tiny Face Detector.
The input image.
(optional, default: see TinyFaceDetectorOptions constructor for default parameters).
Bounding box of each face with score.
Attempts to detect all faces in an image using the Tiny Yolov2 Network.
The input image.
(optional, default: see TinyYolov2Options constructor for default parameters).
Bounding box of each face with score.
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Computes a 128 entry vector (face descriptor / face embeddings) from the face shown in an image, which uniquely represents the features of that persons face. The computed face descriptor can be used to measure the similarity between faces, by computing the euclidean distance of two face descriptors.