python - About "PIL" error, NameError: name 'PIL' is not defined -

i new python user , new 1 in "stack overflow", when try compile tensorflow code met question, , can't found answer website, want helps here, thank in advance!

and compiling result:

d:\python\anaconda2\envs\tensorflow\python.exe d:/python/pycharm_project/test/mnist_chuji traceback (most recent call last):     file "d:/python/pycharm_project/test/mnist_chuji", line 52, in <module>       displayarray(u_init, rng=[-0.1, 0.1])     file "d:/python/pycharm_project/test/mnist_chuji", line 15, in displayarray       pil.image.fromarray(a).save(f, fmt) nameerror: name 'pil' not defined  process finished exit code 1  

here code, , marked line number errors happened make finding easily:

#导入模拟仿真需要的库 import tensorflow tf import numpy np  #导入可视化需要的库 pil import image io import stringio #python3 使用了io代替了sstringio ipython.display import clear_output, image, display  def displayarray(a, fmt='jpeg', rng=[0,1]):   """display array picture."""   = (a - rng[0])/float(rng[1] - rng[0])*255   = np.uint8(np.clip(a, 0, 255))   f = stringio()   pil.image.fromarray(a).save(f, fmt) #line 15   display(image(data=f.getvalue()))  sess = tf.interactivesession()  def make_kernel(a):   """transform 2d array convolution kernel"""   = np.asarray(a)   = a.reshape(list(a.shape) + [1,1])   return tf.constant(a, dtype=1)  def simple_conv(x, k):   """a simplified 2d convolution operation"""   x = tf.expand_dims(tf.expand_dims(x, 0), -1)   y = tf.nn.depthwise_conv2d(x, k, [1, 1, 1, 1], padding='same')   return y[0, :, :, 0]  def laplace(x):   """compute 2d laplacian of array"""   laplace_k = make_kernel([[0.5, 1.0, 0.5],                            [1.0, -6., 1.0],                            [0.5, 1.0, 0.5]])   return simple_conv(x, laplace_k)  n = 500  # initial conditions -- rain drops hit pond  # set 0 u_init = np.zeros([n, n], dtype="float32") ut_init = np.zeros([n, n], dtype="float32")  # rain drops hit pond @ random points n in range(40):   a,b = np.random.randint(0, n, 2)   u_init[a,b] = np.random.uniform()  displayarray(u_init, rng=[-0.1, 0.1]) #line 52  # parameters: # eps -- time resolution # damping -- wave damping eps = tf.placeholder(tf.float32, shape=()) damping = tf.placeholder(tf.float32, shape=())  # create variables simulation state u  = tf.variable(u_init) ut = tf.variable(ut_init)  # discretized pde update rules u_ = u + eps * ut ut_ = ut + eps * (laplace(u) - damping * ut)  # operation update state step = tf.group(   u.assign(u_),   ut.assign(ut_))  # initialize state initial conditions tf.initialize_all_variables().run()  # run 1000 steps of pde in range(1000):   # step simulation   step.run({eps: 0.03, damping: 0.04})   # visualize every 50 steps   if % 50 == 0:     clear_output()     displayarray(u.eval(), rng=[-0.1, 0.1]) 

and have install pillow in tensorflow environment(python 3.5.2).

thank much!

use image.fromarray, since image imported pil pil never imported.