b_test_img_paths,
batch_size,
load_size=load_size,
crop_size=crop_size)
a2b_pool = utils.ItemPool()
b2a_pool = utils.ItemPool()
'''summary'''
summary_writer = tf.summary.FileWriter('./summaries/' + dataset + '_spgan',
sess.graph)
'''saver'''
ckpt_dir = './checkpoints/' + dataset + '_spgan'
utils.mkdir(ckpt_dir + '/')
saver = tf.train.Saver(max_to_keep=30)
ckpt_path = utils.load_checkpoint(ckpt_dir, sess, saver)
if ckpt_path is None:
sess.run(tf.global_variables_initializer())
else:
print('Copy variables from % s' % ckpt_path)
'''train'''
try:
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
batch_epoch = min(len(a_data_pool), len(b_data_pool)) // batch_size
max_it = epoch * batch_epoch
now = time.strftime("%c")
print('================ Begining Training time (%s) ================\n' %
now)
for it in range(sess.run(it_cnt), max_it):
b_test_img_paths = glob('./Datasets/' + dataset + '/bounding_box_train-Market/*.jpg')
a_test_pool = data.ImageData(sess, a_test_img_paths, batch_size, load_size=load_size, crop_size=crop_size)
b_test_pool = data.ImageData(sess, b_test_img_paths, batch_size, load_size=load_size, crop_size=crop_size)
a2b_pool = utils.ItemPool()
b2a_pool = utils.ItemPool()
'''summary'''
summary_writer = tf.summary.FileWriter('./summaries/' + dataset + '_spgan' , sess.graph)
'''saver'''
ckpt_dir = './checkpoints/' + dataset + '_spgan'
utils.mkdir(ckpt_dir + '/')
saver = tf.train.Saver(max_to_keep= 30)
ckpt_path = utils.load_checkpoint(ckpt_dir, sess, saver)
if ckpt_path is None:
sess.run(tf.global_variables_initializer())
else:
print('Copy variables from % s' % ckpt_path)
'''train'''
try:
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
batch_epoch = min(len(a_data_pool), len(b_data_pool)) // batch_size
max_it = epoch * batch_epoch
now = time.strftime("%c")
print('================ Begining Training time (%s) ================\n' % now)
for it in range(sess.run(it_cnt), max_it):
dataset = args.dataset
crop_size = args.crop_size
""" run """
with tf.Session() as sess:
a_real = tf.placeholder(tf.float32, shape=[None, crop_size, crop_size, 3])
b_real = tf.placeholder(tf.float32, shape=[None, crop_size, crop_size, 3])
a2b = models.generator(a_real, 'a2b')
b2a = models.generator(b_real, 'b2a')
b2a2b = models.generator(b2a, 'a2b', reuse=True)
a2b2a = models.generator(a2b, 'b2a', reuse=True)
#--retore--#
saver = tf.train.Saver()
ckpt_path = utils.load_checkpoint('./checkpoints/' + dataset + '_spgan',
sess, saver)
saver.restore(sess, ckpt_path)
if ckpt_path is None:
raise Exception('No checkpoint!')
else:
print('Copy variables from % s' % ckpt_path)
#--test--#
b_list = glob('./Datasets/' + dataset + '/bounding_box_train-Market/*.jpg')
a_list = glob('./Datasets/' + dataset + '/bounding_box_train-Duke/*.jpg')
b_save_dir = './test_predictions/' + dataset + '_spgan' + '/bounding_box_train_market2duke/'
a_save_dir = './test_predictions/' + dataset + '_spgan' + '/bounding_box_train_duke2market/'
utils.mkdir([a_save_dir, b_save_dir])
crop_size = args.crop_size
""" run """
with tf.Session() as sess:
a_real = tf.placeholder(tf.float32, shape=[None, crop_size, crop_size, 3])
b_real = tf.placeholder(tf.float32, shape=[None, crop_size, crop_size, 3])
a2b = models.generator(a_real, 'a2b')
b2a = models.generator(b_real, 'b2a')
b2a2b = models.generator(b2a, 'a2b', reuse=True)
a2b2a = models.generator(a2b, 'b2a', reuse=True)
#--retore--#
saver = tf.train.Saver()
ckpt_path = utils.load_checkpoint('./checkpoints/' + dataset + '_spgan', sess, saver)
saver.restore(sess, ckpt_path)
if ckpt_path is None:
raise Exception('No checkpoint!')
else:
print('Copy variables from % s' % ckpt_path)
#--test--#
b_list = glob('./Datasets/' + dataset + '/bounding_box_train-Market/*.jpg')
a_list = glob('./Datasets/' + dataset + '/bounding_box_train-Duke/*.jpg')
b_save_dir = './test_predictions/' + dataset + '_spgan' + '/bounding_box_train_market2duke/'
a_save_dir = './test_predictions/' + dataset + '_spgan' + '/bounding_box_train_duke2market/'
utils.mkdir([a_save_dir, b_save_dir])