Function plot_topk_histogram

slowfast/visualization/utils.py:92–155

Plot histogram of top-k value from the given array. Args: tag (str): histogram title. array (tensor): a tensor to draw top k value from. k (int): number of top values to draw from array. Defaut to 10. class_names (list of strings, optional):

(tag, array, k=10, class_names=None, figsize=None)

def plot_topk_histogram(tag, array, k=10, class_names=None, figsize=None):
    """
    Plot histogram of top-k value from the given array.
    Args:
        tag (str): histogram title.
        array (tensor): a tensor to draw top k value from.
        k (int): number of top values to draw from array.
            Defaut to 10.
        class_names (list of strings, optional):
            a list of names for values in array.
        figsize (Optional[float, float]): the figure size of the confusion matrix.
            If None, default to [6.4, 4.8].
    Returns:
        fig (matplotlib figure): a matplotlib figure of the histogram.
    """
    val, ind = torch.topk(array, k)

    fig = plt.Figure(figsize=figsize, facecolor="w", edgecolor="k")

    ax = fig.add_subplot(1, 1, 1)

    if class_names is None:
        class_names = [str(i) for i in ind]
    else:
        class_names = [class_names[i] for i in ind]

    tick_marks = np.arange(k)
    width = 0.75
    ax.bar(
        tick_marks,
        val,
        width,
        color="orange",
        tick_label=class_names,
        edgecolor="w",
        linewidth=1,
    )

    ax.set_xlabel("Candidates")
    ax.set_xticks(tick_marks)
    ax.set_xticklabels(class_names, rotation=-45, ha="center")
    ax.xaxis.set_label_position("bottom")
    ax.xaxis.tick_bottom()

    y_tick = np.linspace(0, 1, num=10)
    ax.set_ylabel("Frequency")
    ax.set_yticks(y_tick)
    y_labels = [format(i, ".1f") for i in y_tick]
    ax.set_yticklabels(y_labels, ha="center")

    for i, v in enumerate(val.numpy()):
        ax.text(
            i - 0.1,
            v + 0.03,
            format(v, ".2f"),
            color="orange",
            fontweight="bold",
        )