Python cv2 模块，FILLED 实例源码

def display_detected(self, frame, face_locs, people, confidence):
        """
        - Display ROI's of detected faces with labels
        :param frame:
        :param face_locs:
        :param people : people in image classified
        :param confidence : recognition confidence
        :return:
        """

        if not len(face_locs) == 0:  # nothing detected
            for (top, right, bottom, left), name, conf in zip(face_locs, people, confidence):
                # Scale back up face locations since the frame we detected in was scaled to 1/4 size
                top
                right
                bottom
                left

                # string
                conf_4f = "%.3f" % conf
                peop_conf = "{} {}%".format(name, float(conf_4f) * 100)

                # Draw a box around the face
                cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

                # Draw a label with a name below the face
                # cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
                cv2.rectangle(frame, (left, top + 20), (right, top), (0, 0, 255), cv2.FILLED)

                font = cv2.FONT_HERSHEY_DUPLEX  # color
                # cv2.putText(frame, peop_conf , (left + 6, bottom - 6), font, 0.5, (255, 255, 255), 1)
                cv2.putText(frame, peop_conf, (left, top + 15), font, 0.5, (255, 255, 255), 1)
        pass

def render_bboxes_image(bboxes, output_width, output_height, input_width, input_height):
    '''
    Render the bounding boxes (bboxes) on an image of size (output_width, output_height),
    where the bounding box coordinates exist between (0,0) and (input_width, input_height).
    '''
    output_image = np.zeros((output_height, output_width), dtype=np.uint8)

    w_scale = output_width/input_width
    h_scale = output_height/input_height
    for min_x, min_y, max_x, max_y in bboxes:
        pt1 = (int(min_x*w_scale), int(min_y*h_scale))
        pt2 = (int(max_x*w_scale), int(max_y*h_scale))
        cv2.rectangle(output_image,pt1, pt2, 255, cv2.FILLED)
    return output_image