python - 如何在 Mandlebrot tensorflow 程序中显示图像。当前输出是

Question

'''导入模拟库'''

import tensorflow as tf
import numpy as np

'''为可视化导入'''

from PIL.Image
from io import BytesIO
from IPython.display import Image, display

'''现在我们将定义一个函数来实际显示图像 迭代次数'''

def DisplayFractal(a, fmt='jpeg'):

    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
print(Z)
#Now we define and initialize TensorFlow tensors.

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()

zs_ = zs*zs + xs
print(zs)

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

'''更新 zs 和迭代计数的操作。注意:我们在它们发散后继续计算 zs!这很浪费!有更好的，如果有一点不太简单，方法来做到这一点。''' 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())

Answer 1

我遇到了同样的问题。您必须在 Jupyter notebook 中运行 TensorFlow 示例: http://jupyter.org/

如果您从其他 IDE(例如(Spyder))运行它，您将看到的是 <IPython.core.display.Image object>在控制台中。