Question

我试图获取代码的输出，但错误在with tf.control_dependencies()。错误如下所示：原始代码来自enter link description here

Traceback (most recent call last):
  File "croptest.py", line 80, in <module>
    crop(Image,boxes,batch_inds);
  File "croptest.py", line 55, in crop
    with tf.control_dependencies([assert_op, images, batch_inds]):
  File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3936, in control_dependencies
    return get_default_graph().control_dependencies(control_inputs)
  File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3665, in control_dependencies
    c = self.as_graph_element(c)
  File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2708, in as_graph_element
    return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
  File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2797, in _as_graph_element_locked
    % (type(obj).__name__, types_str))
TypeError: Can not convert a list into a Tensor or Operation.

我相信代码没有错误，我只是好奇控制依赖关系是如何工作的，即使是所有输入都是如此。我运行的代码如下：

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import tensorflow as tf
import numpy as np

def crop(images, boxes, batch_inds, stride = 1, pooled_height = 2, pooled_width = 2, scope='ROIAlign'):
  """Cropping areas of features into fixed size
  Params:
  --------
  images: a 4-d Tensor of shape (N, H, W, C)
  boxes: rois in the original image, of shape (N, ..., 4), [x1, y1, x2, y2]
  batch_inds: 

  Returns:
  --------
  A Tensor of shape (N, pooled_height, pooled_width, C)
  """
  with tf.name_scope(scope):
    #
    boxes = boxes / (stride + 0.0)
    print("boxes again=",boxes)
    boxes = tf.reshape(boxes, [-1, 4])
    print ("2=======================================================")
    print("boxes again=",boxes)
    # normalize the boxes and swap x y dimensions
    shape = tf.shape(images)
    boxes = tf.reshape(boxes, [-1, 2]) # to (x, y)
    print ("3=======================================================")
    print(boxes)
    xs = boxes[:, 0] 
    ys = boxes[:, 1]
    print ("4=======================================================")
    print(xs,ys)
    xs = xs / tf.cast(shape[2], tf.float32)
    ys = ys / tf.cast(shape[1], tf.float32)
    print ("5=======================================================")
    print("again xs,ys",xs,ys)
    boxes = tf.concat([ys[:, tf.newaxis], xs[:, tf.newaxis]], axis=1)
    boxes = tf.reshape(boxes, [-1, 4])  # to (y1, x1, y2, x2)
    print ("6=======================================================")
    print("again boxes", boxes)
     #if batch_inds is False:
    #   num_boxes = tf.shape(boxes)[0]
    #   batch_inds = tf.zeros([num_boxes], dtype=tf.int32, name='batch_inds')
    #   batch_inds = boxes[:, 0] * 0
    #   batch_inds = tf.cast(batch_inds, tf.int32)

    # assert_op = tf.Assert(tf.greater(tf.shape(images)[0], tf.reduce_max(batch_inds)), [images, batch_inds])
    assert_op = tf.Assert(tf.greater(tf.size(images), 0), [images, batch_inds])
    print ("7=======================================================")
    print("assert_op", assert_op)
    print ("8=======================================================")
    with tf.control_dependencies([assert_op, images, batch_inds]):
        return  tf.image.crop_and_resize(images, boxes, batch_inds,
                                         [pooled_height, pooled_width],
                                         method='bilinear',
                                         name='Crop')

这是我设置的输入：

Image =[[[[1, 1, 1,1], [2, 2, 2,2]], [[3,3, 3, 3], [4,4, 4, 4]]]]
print ("=======================================================")
box =  [[1, 1, 2, 2]]
boxes = tf.constant(box, tf.float32)
batch_inds=[1]
batch_inds = np.zeros((4,), dtype=np.int32)
batch_inds = tf.convert_to_tensor(batch_inds)
print("boxes=", boxes)
print (Image)
print(tf.shape(Image));

crop(Image,boxes,batch_inds);

如果我不想修改crop()功能，我的输入有什么问题？谢谢。

Answer 1

我通过添加

解决了这个问题在tf.convert_to_tensor (Image)

之后

Image =[[[[1, 1, 1,1], [2, 2, 2,2]], [[3,3, 3, 3], [4,4, 4, 4]]]]

TypeError：无法将列表转换为Tensor或Operation

1 个答案: