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)