补全代码def compute_accuracy(mask_gt, mask): """ Compute the pixel-wise accuracy of a foreground-background segmentation given a ground truth segmentation. Args: mask_gt - The ground truth foreground-background segmentation. A logical of size H x W where mask_gt[y, x] is 1 if and only if pixel (y, x) of the original image was part of the foreground. mask - The estimated foreground-background segmentation. A logical array of the same size and format as mask_gt. Returns: accuracy - The fraction of pixels where mask_gt and mask agree. A bigger number is better, where 1.0 indicates a perfect segmentation. """ accuracy = None ### YOUR CODE HERE ### END YOUR CODE return accuracy

以下是代码的实现：

def compute_accuracy(mask_gt, mask):
    """ Compute the pixel-wise accuracy of a foreground-background segmentation
        given a ground truth segmentation.
    Args:
        mask_gt - The ground truth foreground-background segmentation. A
            logical of size H x W where mask_gt[y, x] is 1 if and only if
            pixel (y, x) of the original image was part of the foreground.
        mask - The estimated foreground-background segmentation. A logical
            array of the same size and format as mask_gt.
    Returns:
        accuracy - The fraction of pixels where mask_gt and mask agree. A
            bigger number is better, where 1.0 indicates a perfect segmentation.
    """
    accuracy = (mask_gt == mask).mean()
    return accuracy

其中， `(mask_gt == mask)` 返回一个逻辑数组，表示 mask_gt 与 mask 是否相等，然后使用 `.mean()` 方法获取逻辑数组中 True 元素的比例，即为准确率。