(img,
                       result,
                       class_names,
                       score_thr=0.3,
                       fig_size=(15, 10))
Visualize the detection results on the image.

    Args:
        img (str or np.ndarray): Image filename or loaded image.
        result (tuple[list] or list): The detection result, can be either
            (bbox, segm) or just bbox.
        class_names (list[str] or tuple[str]): A list of class names.
        score_thr (float): The threshold to visualize the bboxes and masks.
        fig_size (tuple): Figure size of the pyplot figure.
        out_file (str, optional): If specified, the visualization result will
            be written to the out file instead of shown in a window.
Visualize the detection results on the image.
Visualize the detection results on the image .
def show_result_pyplot(img,
                       result,
                       class_names,
                       score_thr=0.3,
                       fig_size=(15, 10)):
    """Visualize the detection results on the image.

    Args:
        img (str or np.ndarray): Image filename or loaded image.
        result (tuple[list] or list): The detection result, can be either
            (bbox, segm) or just bbox.
        class_names (list[str] or tuple[str]): A list of class names.
        score_thr (float): The threshold to visualize the bboxes and masks.
        fig_size (tuple): Figure size of the pyplot figure.
        out_file (str, optional): If specified, the visualization result will
            be written to the out file instead of shown in a window.
    """
    img = show_result(
        img, result, class_names, score_thr=score_thr, show=False)
    plt.figure(figsize=fig_size)
    plt.imshow(mmcv.bgr2rgb(img))
def show_result_pyplot ( img , result , class_names , score_thr = 0.3 , fig_size = ( 15 , 10 ) ) : img = show_result ( img , result , class_names , score_thr = score_thr , show = False ) plt . figure ( figsize = fig_size ) plt . imshow ( mmcv . bgr2rgb ( img ) )