Question

学习如何使用tensorflow，第一个教程代码在mandelbrot下面设置

# Import libraries for simulation
import tensorflow as tf
import numpy as np

# Imports for visualization
import PIL.Image
from io import BytesIO
from IPython.display import Image, display

def DisplayFractal(a, fmt='jpeg'):
  """Display an array of iteration counts as a
     colorful picture of a fractal."""
  a_cyclic = (6.28*a/20.0).reshape(list(a.shape)+[1])
  img = np.concatenate([10+20*np.cos(a_cyclic),
                        30+50*np.sin(a_cyclic),
                        155-80*np.cos(a_cyclic)], 2)
  img[a==a.max()] = 0
  a = img
  a = np.uint8(np.clip(a, 0, 255))
  f = BytesIO()
  PIL.Image.fromarray(a).save(f, fmt)
  display(Image(data=f.getvalue()))


sess = tf.InteractiveSession()

# Use NumPy to create a 2D array of complex numbers

Y, X = np.mgrid[-1.3:1.3:0.005, -2:1:0.005]
Z = X+1j*Y

xs = tf.constant(Z.astype(np.complex64))
zs = tf.Variable(xs)
ns = tf.Variable(tf.zeros_like(xs, tf.float32))

tf.global_variables_initializer().run()


# Compute the new values of z: z^2 + x
zs_ = zs*zs + xs

# Have we diverged with this new value?
not_diverged = tf.abs(zs_) < 4

# Operation to update the zs and the iteration count.
#
# Note: We keep computing zs after they diverge! This
#       is very wasteful! There are better, if a little
#       less simple, ways to do this.
#
step = tf.group(
  zs.assign(zs_),
  ns.assign_add(tf.cast(not_diverged, tf.float32))
  )


for i in range(200): step.run()

DisplayFractal(ns.eval())

在shell上返回

<IPython.core.display.Image at 0x7fcdee1da810>

它不显示图像，我更喜欢它保存图像。如何将结果保存为图像？

Answer 1

Scipy具有简单的图像保存功能！ https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.misc.imsave.html

你应该试试这个：

import scipy.misc
scipy.misc.imsave('mandelbrot.png',ns.eval())

我希望这有效！无论如何，请告诉我！

TensorFlow示例保存mandelbrot图像

1 个答案: