[英]Cannot print the value of tensor
運行代碼時出現以下錯誤。 我想知道張量為“ feat”的張量的價值。
Traceback (most recent call last):
File "croptest.py", line 80, in <module>
print (sess.run(feat))
File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 895, in run
run_metadata_ptr)
File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1124, in _run
feed_dict_tensor, options, run_metadata)
File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1321, in _do_run
options, run_metadata)
File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: box_ind has values outside [0, batch)
[[Node: ROIAlign/Crop = CropAndResize[T=DT_UINT8, extrapolation_value=0, method="bilinear", _device="/job:localhost/replica:0/task:0/cpu:0"](ROIAlign/Crop/image, ROIAlign/Reshape_2, ROIAlign/Crop/box_ind, ROIAlign/Crop/crop_size)]]
Caused by op u'ROIAlign/Crop', defined at:
File "croptest.py", line 73, in <module>
feat =crop(img, boxes, batch_inds,16,7,7,'ROIAlign')
File "croptest.py", line 64, in crop
name='Crop')
File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/ops/gen_image_ops.py", line 166, in crop_and_resize
name=name)
File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/ubuntu/Desktop/WK/my_project/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1204, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
OutOfRangeError (see above for traceback): box_ind has values outside [0, batch)
[[Node: ROIAlign/Crop = CropAndResize[T=DT_UINT8, extrapolation_value=0, method="bilinear", _device="/job:localhost/replica:0/task:0/cpu:0"](ROIAlign/Crop/image, ROIAlign/Reshape_2, ROIAlign/Crop/box_ind, ROIAlign/Crop/crop_size)]]
輸入的圖像是2個RGB圖像; 可以運行“ init = tf.global_variables_initializer()”之前的所有代碼,我打印張量的方式是否錯誤? 任何更好的方式來打印張量。 下面是我運行的代碼:
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import glob
import tensorflow as tf
import numpy as np
import cv2
def crop(images, boxes, batch_inds, stride, pooled_height, pooled_width, scope):
"""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)
"""
#print(tf.shape(images))
with tf.name_scope(scope):
boxes = [x / (stride+0.0) for x in boxes]
boxes = tf.reshape(boxes, [-1, 4])
print(images)
# normalize the boxes and swap x y dimensions
print(images.shape)
shape = tf.shape(images)
boxes = tf.reshape(boxes, [-1, 2]) # to (x, y)
xs = boxes[:, 0]
ys = boxes[:, 1]
xs = xs / tf.cast(shape[2], tf.float32)
ys = ys / tf.cast(shape[1], tf.float32)
boxes = tf.concat([ys[:, tf.newaxis], xs[:, tf.newaxis]], axis=1)
boxes = tf.reshape(boxes, [-1, 4]) # to (y1, x1, y2, x2)
assert_op = tf.Assert(tf.greater(tf.size(images), 0), [images, batch_inds])
print(assert_op)
print("-----------------------")
print(images.astype('float'))
print("-----------------------")
print(batch_inds)
x=images.astype('float')
print("-----------------------")
print(batch_inds)
print("-----------------------")
print(pooled_height)
print("-----------------------")
pools =[pooled_height, pooled_width]
arg = tf.convert_to_tensor(x, dtype=tf.float32)
arg1 = tf.convert_to_tensor(batch_inds)
with tf.control_dependencies([assert_op, arg,arg1 ]):
return tf.image.crop_and_resize(images, boxes, batch_inds,
pools,
method='bilinear',
name='Crop')
images = [cv2.imread(file) for file in glob.glob("/home/ubuntu/Pictures/TeImage/*.png")]
img= np.asarray(images)
boxes = [100, 100, 200, 200]
batch_inds=[2]
feat =crop(img, boxes, batch_inds,16,7,7,'ROIAlign')
init=tf.global_variables_initializer()
sess=tf.Session()
sess.run(init)
print (sess.run(feat))
我認為錯誤可能是由您使用tensorflow.shape引起的,它看起來像是為張量設計的,並且也許image數組的功能不適合此tnesor形式。 但是,如果將tf換為np(bumpy.shape),它應該打印圖像的形狀,並精確地執行要執行的操作,但是輸入具有更大的靈活性。
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