我有一个tensor
看起来像:
Tensor("Identity:0", shape=(10000, 32, 32, 3), dtype=float32)
我想出了如何对其进行迭代:
for adv_x in tf.unstack(adv):
asnumpy = tf.Session().run(tf.unstack(adv_x))
print(asnumpy)
返回:
...
Tensor("unstack:9997", shape=(32, 32, 3), dtype=float32)
Tensor("unstack:9998", shape=(32, 32, 3), dtype=float32)
Tensor("unstack:9999", shape=(32, 32, 3), dtype=float32)
如何获取每个的值并保存为png?
这是
python3.7
和tensorflow1.13
我有一个错误:
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value conv2d_1/kernel
[[{{node conv2d_1/kernel/read}}]]
最佳答案
将其转换为numpy,然后使用scipy.misc.imsave
进行存储
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
asnumpy = sess.run(tf.unstack(adv)) # `asnumpy` stores images as numpy arrays
要存储它:
import scipy.misc
for i, image in enumerate(asnumpy):
scipy.misc.imsave('image' + str(i) + '.png', image)
关于python - 如何将张量图像另存为PNG?,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/55714528/