extractor.py 文件源码

def detect(cls,
               image,
               min_size=(50, 50),
               scale_factor=1.1,
               min_neighbors=5,
               cascade_file=_current_cascade):
        """ Return list of objects detected.
        image -- The image (numpy matrix) read by readImage function.
        min_size -- Minimum possible object size. Objects smaller than that are ignored (default (50,50)).
        scale_factor -- Specifying how much the image size is reduced at each image scale (default 1.1).
        min_neighbors -- Specifying how many neighbors each candidate rectangle should have to retain it (default 5).
        cascade_file  -- The path of cascade xml file use for detection (default current value)
        """

        classifier = cls._classifier
        if cascade_file != cls._current_cascade:
            classifier = cv2.CascadeClassifier(cascade_file)

        gray_image = cls.bgr_to_gray(image)
        return classifier.detectMultiScale(gray_image,
                                           scaleFactor=scale_factor,
                                           minNeighbors=min_neighbors,
                                           minSize=min_size)