def main(_):
data = DIV2K2018(train_data_dir=FLAGS.datadir,
image_size=FLAGS.imgsize,
train_truth_dir=FLAGS.groundtruthdir,
test_data_dir=FLAGS.valid_datadir,
test_truth_dir=FLAGS.valid_groundtruthdir,
scale=FLAGS.scale,
train_postfix_len=FLAGS.postfixlen,
test_postfix_len=FLAGS.validpostfixlen,
test_per=0.1)
data = NormalizeData(data,
x_normal=(FLAGS.imgsize != FLAGS.waveletimgsize))
dwt_data = WaveletData(data,
wavelet_img_size=FLAGS.waveletimgsize,
wavelet=FLAGS.wavelet)
network = WaveletSR(FLAGS.layers,
FLAGS.featuresize,
FLAGS.scale,
FLAGS.waveletimgsize,
FLAGS.imgsize * FLAGS.scale,
channels=3)
network.buildModel()
network.set_data(dwt_data)
reuse = False if FLAGS.reusedir == None else True
network.train(FLAGS.batchsize,
FLAGS.iterations,
save_dir=FLAGS.savedir,
log_dir=FLAGS.log,
reuse=reuse,
reuse_dir=FLAGS.reusedir,
reuse_epoch=FLAGS.reuseep)
def main(_):
data = DIV2K2018(FLAGS.groundtruthdir, FLAGS.datadir, None, None,
FLAGS.imgsize, FLAGS.scale, FLAGS.postfixlen,
FLAGS.postfixlen)
if (os.path.exists(FLAGS.prunedlist_path)):
prunedlist = np.loadtxt(FLAGS.prunedlist_path, dtype=np.int64)
else:
prunedlist = [0] * 16
#print("========================"+FLAGS.prune)
if (FLAGS.prune):
network = EDSR_P(FLAGS.layers, FLAGS.featuresize, FLAGS.scale,
FLAGS.channels, FLAGS.channels, prunedlist,
FLAGS.prunesize)
else:
network = EDSR(FLAGS.layers, FLAGS.featuresize, FLAGS.scale,
FLAGS.channels, FLAGS.channels, prunedlist,
FLAGS.prunesize)
#network = CycleSR(FLAGS.featuresize, FLAGS.layers, FLAGS.channels)
network.buildModel()
network.set_data(data)
network.train(FLAGS.batchsize,
FLAGS.iterations,
FLAGS.lr_init,
FLAGS.lr_decay,
FLAGS.decay_every,
FLAGS.savedir,
True,
FLAGS.reusedir,
500,
log_dir=FLAGS.logdir)
def main(_):
data = DIV2K2018(FLAGS.datadir, FLAGS.groundtruthdir, FLAGS.imgsize,
FLAGS.scale, FLAGS.postfixlen)
network = DenseNet(FLAGS.imgsize, FLAGS.denseblock, FLAGS.growthrate,
FLAGS.bottlenecksize, FLAGS.layers, FLAGS.featuresize,
FLAGS.scale)
network.buildModel()
network.set_data(data)
network.train(FLAGS.batchsize, FLAGS.iterations, FLAGS.savedir, False)
def main(_):
data = DIV2K2018(FLAGS.datadir, FLAGS.groundtruthdir, FLAGS.imgsize,
FLAGS.scale, FLAGS.postfixlen)
# scdata = SeparateChannelData(data)
network = EDSR(FLAGS.layers, FLAGS.featuresize, FLAGS.scale, channels=3)
network.buildModel()
network.set_data(data)
network.train(
FLAGS.batchsize,
FLAGS.iterations,
FLAGS.savedir,
True,
)
def main(_):
data = DIV2K2018(FLAGS.groundtruthdir, FLAGS.datadir, None, None,
FLAGS.imgsize, FLAGS.scale, FLAGS.postfixlen,
FLAGS.postfixlen)
if (os.path.exists(FLAGS.prunedlist_path)):
prunedlist = np.loadtxt(FLAGS.prunedlist_path, dtype=np.int64)
else:
prunedlist = [0] * 19
network = EDSR(FLAGS.layers, FLAGS.featuresize, FLAGS.scale,
FLAGS.channels, FLAGS.channels, prunedlist)
network.buildModel()
network.set_data(data)
network.train(FLAGS.batchsize, FLAGS.iterations, FLAGS.lr_init,
FLAGS.lr_decay, FLAGS.decay_every, FLAGS.savedir,
FLAGS.reuse, FLAGS.reusedir, FLAGS.model_step, FLAGS.logdir,
FLAGS.prune, FLAGS.prunesize, FLAGS.prune_method, False)
def main(_):
data = DIV2K2018(FLAGS.groundtruthdir, FLAGS.datadir, None, None,
FLAGS.imgsize, FLAGS.scale, FLAGS.postfixlen,
FLAGS.postfixlen)
#adddata = AddData(data, ratio=0.2)
network = EDSR(FLAGS.layers, FLAGS.featuresize, FLAGS.scale,
FLAGS.channels, FLAGS.channels, FLAGS.prunedsize,
FLAGS.prunesize, FLAGS.prunedlist)
#network = CycleSR(FLAGS.featuresize, FLAGS.layers, FLAGS.channels)
network.buildModel()
network.set_data(data)
network.train(FLAGS.batchsize,
FLAGS.iterations,
FLAGS.lr_init,
FLAGS.lr_decay,
FLAGS.decay_every,
FLAGS.savedir,
True,
FLAGS.reusedir,
500,
log_dir=FLAGS.logdir)
def main(_):
data = DIV2K2018(FLAGS.groundtruthdir, FLAGS.datadir,
FLAGS.valid_groundtruthdir, FLAGS.valid_datadir,
FLAGS.imgsize, FLAGS.scale, FLAGS.postfixlen)
network = EDSR(n_channels=FLAGS.n_channels)
network.build_model(FLAGS.n_features,
FLAGS.n_res_blocks,
FLAGS.scale,
max_to_keep=FLAGS.max_to_keep)
network.set_data(data)
network.train(FLAGS.batchsize,
FLAGS.iterations,
FLAGS.test_every,
FLAGS.lr_init,
FLAGS.lr_decay,
FLAGS.decay_every,
FLAGS.savedir,
False,
FLAGS.reusedir,
None,
log_dir=FLAGS.logdir)