python之无法将 tensorflow 图像保存到文件

我需要将图像调整到特定大小并将其保存到文件中，所以我选择了 tf.image.resize_image_with_crop_or_pad 函数:

import tensorflow as tf 
 
image_decoded = tf.image.decode_jpeg(tf.read_file('1.jpg'), channels=3) 
cropped       = tf.image.resize_image_with_crop_or_pad(image_decoded, 200, 200) 
tf.write_file('2.jpg', cropped) 

因错误而失败:

Traceback (most recent call last): 
  File "/home/test/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 490, in apply_op 
    preferred_dtype=default_dtype) 
  File "/home/test/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 669, in convert_to_tensor 
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) 
  File "/home/test/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 583, in _TensorTensorConversionFunction 
    % (dtype.name, t.dtype.name, str(t))) 
ValueError: Tensor conversion requested dtype string for Tensor with dtype uint8: 'Tensor("control_dependency_3:0", shape=(200, 200, 3), dtype=uint8)' 
 
During handling of the above exception, another exception occurred: 
 
Traceback (most recent call last): 
  File "train.py", line 15, in <module> 
    tf.write_file('2.jpg', cropped) 
  File "/home/test/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/gen_io_ops.py", line 694, in write_file 
    contents=contents, name=name) 
  File "/home/test/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 508, in apply_op 
    (prefix, dtypes.as_dtype(input_arg.type).name)) 
TypeError: Input 'contents' of 'WriteFile' Op has type uint8 that does not match expected type of string. 

我尝试使用 tf.as_string() 将 Tensor 转换为字符串，但崩溃了:

TypeError: DataType uint8 for attr 'T' not in list of allowed values: int32, int64, complex64, float32, float64, bool, int8 

我在 Linux Mint 上使用 Tensorflow v0.12.0-rc0

请您参考如下方法:

您首先需要将图像从张量编码为 jpeg，然后保存。此外，您应该执行一个 session 来评估您的代码:

import tensorflow as tf 
 
image_decoded = tf.image.decode_jpeg(tf.read_file('1.jpg'), channels=3) 
cropped       = tf.image.resize_image_with_crop_or_pad(image_decoded, 200, 200) 
enc = tf.image.encode_jpeg(cropped) 
fname = tf.constant('2.jpg') 
fwrite = tf.write_file(fname, enc) 
 
sess = tf.Session() 
result = sess.run(fwrite) 

编辑:与 TensorFlow 2 相同(兼容模式)

fname = '2.jpg' 
with tf.compat.v1.Session() as sess: 
    image_decoded = tf.image.decode_jpeg(tf.io.read_file('1.jpg'), channels=3) 
    cropped = tf.image.resize_with_crop_or_pad(image_decoded, 200, 200) 
    enc = tf.image.encode_jpeg(cropped) 
    fwrite = tf.io.write_file(tf.constant(fname), enc) 
    result = sess.run(fwrite)