尝试从图像中提取补丁并得到“UnimplementedError：只支持跨空间的 ksizes”

Question

当我遇到以下错误时，我试图通过 4 个补丁拆分我的图像：

UnimplementedError: Only support ksizes across space

iterator = tf.compat.v1.data.make_one_shot_iterator(parsed_dataset) 

image,label = iterator.get_next()

image_height = image.shape[0]

image_width = image.shape[1]

# Since the expected type is (batch,height,width,channels), i have tryied to expand my image that have

# dimensions: (800,344,3) to (1,800,344,3) but didn't solved the error.

#image = tf.expand_dims(image ,0)

images = list(image)

extracted_patches = tf.image.extract_patches(images=images,

                                             sizes=[1,int(0.25*image_height),int(0.25*image_width),3],

                                             strides=[1,int(0.25*image_height),int(0.25*image_width),3],

                                             rates=[1,1,1,1],

                                             padding="SAME")

追溯：

---------------------------------------------------------------------------

UnimplementedError                        Traceback (most recent call last)

<ipython-input-64-23c2aff4c306> in <module>()

     17                                              strides=[1,int(0.25*image_height),int(0.25*image_width),3],

     18                                              rates=[1,1,1,1],

---> 19                                              padding="SAME")

     20 

     21 

/Users/lucianoaraujo/anaconda2/lib/python2.7/site-packages/tensorflow_core/python/ops/array_ops.pyc in extract_image_patches_v2(images, sizes, strides, rates, padding, name)

   4657   """

   4658   return gen_array_ops.extract_image_patches(images, sizes, strides, rates,

-> 4659                                              padding, name)

   4660 

   4661 

Answer 1

经过进一步的研究，我能够通过改变来管理：images = list(image)extracted_patches = tf.image.extract_patches(images=images,&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;sizes=[1,int(0.25*image_height),int(0.25*image_width),3],&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;strides=[1,int(0.25*image_height),int(0.25*image_width),3],&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;rates=[1,1,1,1],&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;padding="SAME")到 ：image = tf.expand_dims(image ,0)extracted_patches = tf.image.extract_patches(images=image,&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;sizes=[1,int(0.25*image_height),int(0.25*image_width),1],&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;strides=[1,int(0.25*image_height),int(0.25*image_width),1],&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;rates=[1,1,1,1],&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;padding="SAME")然后重塑以获得3通道图像：patches = tf.reshape(extracted_patches,[-1,int(0.25*image_height),int(0.25*image_width),3])