import os
import numpy as np
import tensorflow as tf
import matplotlib.pylab as plt
FLAGS = tf.app.flags.FLAGS
def save_image(data, data_format, e, suffix=None):
"""Saves a picture showing the current progress of the model"""
X_G, X_real = data
Xg = X_G[:8]
Xr = X_real[:8]
if data_format == "NHWC":
X = np.concatenate((Xg, Xr), axis=0)
list_rows = []
for i in range(int(X.shape[0] / 4)):
Xr = np.concatenate([X[k] for k in range(4 * i, 4 * (i + 1))], axis=1)
list_rows.append(Xr)
Xr = np.concatenate(list_rows, axis=0)
if data_format == "NCHW":
X = np.concatenate((Xg, Xr), axis=0)
list_rows = []
for i in range(int(X.shape[0] / 4)):
Xr = np.concatenate([X[k] for k in range(4 * i, 4 * (i + 1))], axis=2)
list_rows.append(Xr)
Xr = np.concatenate(list_rows, axis=1)
Xr = Xr.transpose(1,2,0)
if Xr.shape[-1] == 1:
plt.imshow(Xr[:, :, 0], cmap="gray")
else:
plt.imshow(Xr)
plt.axis("off")
if suffix is None:
plt.savefig(os.path.join(FLAGS.fig_dir, "current_batch_%s.png" % e))
else:
plt.savefig(os.path.join(FLAGS.fig_dir, "current_batch_%s_%s.png" % (suffix, e)))
plt.clf()
plt.close()
def get_stacked_tensor(X1, X2):
X = tf.concat((X1[:16], X2[:16]), axis=0)
list_rows = []
for i in range(8):
Xr = tf.concat([X[k] for k in range(4 * i, 4 * (i + 1))], axis=2)
list_rows.append(Xr)
X = tf.concat(list_rows, axis=1)
X = tf.transpose(X, (1,2,0))
X = tf.expand_dims(X, 0)
return X
