DetectorFace¶

class DetectorFace(self)¶

Bases: DetectorBase

The vpDetectorFace class is a wrapper over OpenCV Haar cascade face detection capabilities. To use this class ViSP should be build against OpenCV 2.2.0 or a more recent version. Installation instructions are provided here https://visp.inria.fr/3rd_opencv .

The following sample code shows how to use this class to detect the largest face in the image. The cascade classifier file “haarcascade_frontalface_alt.xml” can be found in ViSP source code or in OpenCV.

#include <visp3/detection/vpDetectorFace.h>

int main()
{
#if defined(VISP_HAVE_OPENCV) && defined(HAVE_OPENCV_OBJDETECT)
  vpImage<unsigned char> I;
  vpDetectorFace face_detector;
  face_detector.setCascadeClassifierFile("haarcascade_frontalface_alt.xml");

  while(1) {
    // Acquire a new image in I
    bool face_found = face_detector.detect(I);
    if (face_found) {
      vpRect face_bbox = face_detector.getBBox(0); // largest face has index 0
    }
  }
#endif
}

A more complete example that works with images acquired from a camera is provided in tutorial-face-detector-live.cpp.

Default constructor.

Methods

`__init__`	Default constructor.
`detect`	Overloaded function.
`setCascadeClassifierFile`	Set the name of the OpenCV cascade classifier file used for face detection.

Inherited Methods

`getCog`	Return the center of gravity location of the ith object.
`getPolygon`	Overloaded function.
`getBBox`	Return the bounding box of the ith object.
`getNbObjects`	Return the number of objects that are detected.
`getMessage`	Overloaded function.
`setTimeout`	Set detector timeout in milli-seconds.

Operators

`__doc__`
`__init__`	Default constructor.
`__module__`

Attributes

`__annotations__`

__init__(self)¶: Default constructor.

detect(*args, **kwargs)¶

Overloaded function.

detect(self: visp._visp.detection.DetectorFace, I: visp._visp.core.ImageGray) -> bool

Allows to detect a face in the image. When more than one face is detected, faces are sorted from largest to smallest.

The number of detected faces is returned using getNbObjects() . If a face is found the functions getBBox() , getCog() return some information about the location of the face.

The largest face is always available using getBBox(0) or getCog(0).

Note

See detect(const cv::Mat &)

Parameters:

I: Input image to process. This ViSP image is converted internally in an OpenCV cv::Mat image. If you original image is an gray level OpenCV image, we suggest rather the use of detect(const cv::Mat &) .

Returns:

true if one or more faces are found, false otherwise.

detect(self: visp._visp.detection.DetectorFace, frame_gray: cv::Mat) -> bool

Allows to detect a face in the image. When more than one face is detected, faces are sorted from largest to smallest.

The number of detected faces is returned using getNbObjects() . If a face is found the functions getBBox() , getCog() return some information about the location of the face.

The largest face is always available using getBBox(0) or getCog(0).

Parameters:

frame_gray: Input gray level image to process.

Returns:

true if one or more faces are found, false otherwise.

getBBox(self, i: int) → visp._visp.core.Rect¶: Return the bounding box of the ith object.

getCog(self, i: int) → visp._visp.core.ImagePoint¶: Return the center of gravity location of the ith object.

getMessage(*args, **kwargs)¶

Overloaded function.

getMessage(self: visp._visp.detection.DetectorBase) -> list[str]

Returns the contained message of the ith object if there is one.

getMessage(self: visp._visp.detection.DetectorBase, i: int) -> str

Returns the contained message of the ith object if there is one.

getNbObjects(self) → int¶: Return the number of objects that are detected.

getPolygon(*args, **kwargs)¶

Overloaded function.

getPolygon(self: visp._visp.detection.DetectorBase) -> list[list[visp._visp.core.ImagePoint]]

Returns object container box as a vector of points.

getPolygon(self: visp._visp.detection.DetectorBase, i: int) -> list[visp._visp.core.ImagePoint]

Returns ith object container box as a vector of points.

setCascadeClassifierFile(self, filename: str) → None¶

Set the name of the OpenCV cascade classifier file used for face detection.

Parameters:

filename: str¶: Full path to access to the file. Such a file can be found in OpenCV. Within the last versions it was name “haarcascade_frontalface_alt.xml”.

setTimeout(self, timeout_ms: int) → None¶: Set detector timeout in milli-seconds. When set to 0, there is no timeout.