def vis_bbox()

in src/SealDetectionRCNN/utils/vis_tool.py [0:0]

• 31 lines of code
• 16 McCabe index (conditional complexity)

def vis_bbox(img, bbox, label=None, score=None, label_names=None, ax=None):
    """Visualize bounding boxes inside image.

    Args:
        img (~numpy.ndarray): An array of shape :math:`(3, height, width)`.
            This is in RGB format and the range of its value is
            :math:`[0, 255]`.
        bbox (~numpy.ndarray): An array of shape :math:`(R, 4)`, where
            :math:`R` is the number of bounding boxes in the image.
            Each element is organized
            by :math:`(y_{min}, x_{min}, y_{max}, x_{max})` in the second axis.
        label (~numpy.ndarray): An integer array of shape :math:`(R,)`.
            The values correspond to id for label names stored in
            :obj:`label_names`. This is optional.
        score (~numpy.ndarray): A float array of shape :math:`(R,)`.
             Each value indicates how confident the prediction is.
             This is optional.
        label_names (iterable of strings): Name of labels ordered according
            to label ids. If this is :obj:`None`, labels will be skipped.
        ax (matplotlib.axes.Axis): The visualization is displayed on this
            axis. If this is :obj:`None` (default), a new axis is created.

    Returns:
        ~matploblib.axes.Axes:
        Returns the Axes object with the plot for further tweaking.

    """

    if label_names is None:
        label_names = list(VOC_BBOX_LABEL_NAMES) + ['bg']
    # add for index `-1`
    if label is not None and not len(bbox) == len(label):
        raise ValueError('The length of label must be same as that of bbox')
    if score is not None and not len(bbox) == len(score):
        raise ValueError('The length of score must be same as that of bbox')

    # Returns newly instantiated matplotlib.axes.Axes object if ax is None
    ax = vis_image(img, ax=ax)

    # If there is no bounding box to display, visualize the image and exit.
    if len(bbox) == 0:
        return ax

    for i, bb in enumerate(bbox):
        xy = (bb[1], bb[0])
        height = bb[2] - bb[0]
        width = bb[3] - bb[1]
        ax.add_patch(plot.Rectangle(
            xy, width, height, fill=False, edgecolor='red', linewidth=2))

        caption = list()

        if label is not None and label_names is not None:
            lb = label[i]
            if not (-1 <= lb < len(label_names)):  # modfy here to add backgroud
                raise ValueError('No corresponding name is given')
            caption.append(label_names[lb])
        if score is not None:
            sc = score[i]
            caption.append('{:.2f}'.format(sc))

        if len(caption) > 0:
            ax.text(bb[1], bb[0],
                    ': '.join(caption),
                    style='italic',
                    bbox={'facecolor': 'white', 'alpha': 0.5, 'pad': 0})
    return ax