CVZone Model Documentation

Documentation for the CVZone-related code.

Link to the library can be found here.

detect_face_cvzone(img, detector, detect_multiple_faces=True)

Function that detects faces in an image using the CVZone library.

Parameters:

Name	Type	Description	Default
img	ndarray	The image in which to detect face. Retrieved by OpenCVs imread function.	required
detector	FaceMeshDetector	An instance of the Face Mesh detector, pretrained from the CVZone library	required
detect_multiple_faces	bool	Will return multiple faces if true, else only one. Default is set to true.	True

Returns:

Type	Description
list | tuple | None	If detect_multiple_faces is true, returns a list of tuples (x, y, width, height) for each detected face. Else returns a single tuple (x, y, width, height) for the most prominent face, or None if no faces are detected. Each tuple represents the top-left corner and dimensions of the bounding box around the detected face.

Each tuple contains the coordinates of the top left corner and the dimensions of the bounding box.

Source code in src/models/code/cvzone.py

def detect_face_cvzone(img: np.ndarray, detector: FaceMeshDetector, detect_multiple_faces=True) -> (list | tuple | None):
    """ Function that detects faces in an image using the CVZone library. 

    Parameters:
        img (np.ndarray): The image in which to detect face. Retrieved by OpenCVs imread function.  
        detector (FaceMeshDetector): An instance of the Face Mesh detector, pretrained from the CVZone library
        detect_multiple_faces (bool, optional): Will return multiple faces if true, else only one. Default is set to true. 

    Returns:
        If `detect_multiple_faces` is true, returns a list of tuples (x, y, width, height) for each detected face. \
        Else returns a single tuple (x, y, width, height) for the most prominent face, or None if no faces are detected. \
        Each tuple represents the top-left corner and dimensions of the bounding box around the detected face.

    Each tuple contains the coordinates of the top left corner and the dimensions of the bounding box.
    """
    _, faces = detector.findFaceMesh(img, draw=False)

    if detect_multiple_faces == True:
        return faces
    return faces[0] if faces else None