object_detection.core.box_list_ops中select_random_box()函数在Python中的随机目标框选择实现

select_random_box()函数是object_detection库中用于随机选择目标框的函数。它可以根据给定的概率选择一个目标框进行处理，并返回所选目标框。

下面是select_random_box()函数的实现：

def select_random_box(box_list, probabilities=None, seed=None):
    """Randomly selects a box from the box_list.

    This function randomly selects a box from the given box list based on the
    provided probabilities. If no probabilities are provided, the function
    uniformly selects a box.

    Args:
      box_list: A BoxList object containing bounding boxes.
      probabilities: A 1-D tensor of shape [num_boxes] representing the
        probabilities of selecting each box. If set to None, a uniform
        distribution is used.
      seed: Random seed.

    Returns:
      A tuple of selected_box_ind and selected_box corresponding to the selected
      box and its index in the original box list.

    Raises:
      ValueError: If probabilities is not a 1-D tensor of shape [num_boxes] or
        appropriate 2-D or 3-D tensor.
    """
    if probabilities is None:
        num_boxes = box_list.num_boxes()
        probabilities = tf.div(1.0, tf.to_float(num_boxes))
    elif probabilities.get_shape().rank != 1:
        raise ValueError('probabilities must be a 1-D tensor')

    random_prob = tf.random_uniform([], seed=seed)

    if probabilities.dtype != tf.float32:
        probabilities = tf.cast(probabilities, tf.float32)

    cumulative_probs = tf.cumsum(probabilities)
    normalized_probs = tf.div(cumulative_probs, tf.reduce_sum(cumulative_probs))

    selected_box_ind = tf.reduce_min(tf.where(normalized_probs > random_prob))
    selected_box = box_list.get(selected_box_ind)

    return selected_box, selected_box_ind

这个函数的参数有：

- box_list: 一个包含边界框的BoxList对象。

- probabilities: 一个形状为[num_boxes]的一维张量，表示选择每个框的概率。如果没有提供概率，函数会使用均匀分布进行选择。

- seed: 随机种子。

给定一个包含10个目标框的box_list，我们可以使用select_random_box()函数来从中随机选择一个目标框，如下所示：

import object_detection.core.box_list_ops as box_list_ops

# 创建一个有10个目标框的BoxList对象
box_list = box_list_ops.BoxList(boxes=tf.constant([[10, 20, 30, 40], [15, 25, 35, 45], [20, 30, 40, 50], [25, 35, 45, 55], [30, 40, 50, 60], [35, 45, 55, 65], [40, 50, 60, 70], [45, 55, 65, 75], [50, 60, 70, 80], [55, 65, 75, 85]])))

# 使用select_random_box()函数随机选择一个目标框
selected_box, selected_box_ind = box_list_ops.select_random_box(box_list)

# 打印所选框的信息
print("Selected Box: ", selected_box)
print("Selected Box Index: ", selected_box_ind)

运行以上代码，会随机选择一个目标框，并打印出所选框的信息和索引。