Question

我要串联三个大小为[1024,1024,3]的图像，以制作大小为[3,1024,1024,3]的批处理。我用TensorFlow编写了此代码，但无法正常工作。它返回错误"InaccessibleTensorError: The tensor 'Tensor("truediv:0", shape=(1024, 1024, 3), dtype=float32)' cannot be accessed here: it is defined in another function or code block. Use return values, explicit Python locals or TensorFlow collections to access it."。

def decode_img(filename):
    image = tf.ones((3,1024,1024,3),dtype=tf.dtypes.float32)
    cnt=0
    slices = []
    for fi in filename:
      bits = tf.io.read_file(fi)
      img = tf.image.decode_jpeg(bits, channels=3)
      img = tf.image.resize(img, (1024,1024))
      slices.append(tf.cast(img, tf.float32) / 255.0)
      cnt +=1

    image = tf.stack(slices)
    return image

#-----------------------
filenames = ['img1.png', 'img2.png', 'img3.png']
dataset = tf.data.Dataset.from_tensor_slices(filenames)
dataset = dataset.map(decode_img, num_parallel_calls=AUTO)

Answer 1

通常，tensorflow不支持项目分配。相反，生成所需的所有img层，然后使用tf.stack()或tf.concatenate。

filename = [img1.png, img2.png, img3.png]
cnt=0
slices = []
for fi in filename:
  bits = tf.io.read_file(fi)
  img = tf.image.decode_jpeg(bits, channels=3)
  img = tf.image.resize(img, (1024,1024))
  slices.append(tf.cast(img, tf.float32) / 255.0)
  cnt +=1

image = tf.stack(slices)

处理矩阵张量流，tf.data.dataset问题

1 个答案: