def main(unused_argv):
if not tf.gfile.IsDirectory(FLAGS.save_dir):
tf.gfile.MakeDirs(FLAGS.save_dir)
with tf.Graph().as_default():
datasets = dataset.get_datasets()
dataset_content = datasets[FLAGS.dataset](FLAGS.dataset,
FLAGS.dataset_split, 4,
128 * 1024)
batched = dataset_content.batch(64)
batch_op = batched.make_one_shot_iterator().get_next()
with tf.Session() as session:
data = session.run(batch_op)[0]
if not FLAGS.grid:
for i in range(data.shape[0]):
save_image(data[i], FLAGS.dataset + "_%d.png" % i)
else:
grid_im = []
for i in range(8):
im_row = []
for j in range(8):
im_row.append(data[i * 8 + j])
grid_im.append(np.concatenate(im_row, axis=1))
grid_im = np.concatenate(grid_im, axis=0)
save_image(grid_im, FLAGS.dataset + "_grid.png")
def main(unused_argv):
gan_lib.MODELS.update({
"MultiGAN": multi_gan.MultiGAN,
"MultiGANBackground": multi_gan_background.MultiGANBackground
})
params.PARAMETERS.update({
"MultiGAN": multi_gan.MultiGANHyperParams,
"MultiGANBackground": multi_gan_background.MultiGANBackgroundHyperParams
})
gan_lib.DATASETS.update(dataset.get_datasets())
params.DATASET_PARAMS.update(dataset.get_dataset_params())
task_workdir = FLAGS.eval_task_workdir
task = simple_task_pb2.Task()
with open(os.path.join(task_workdir, "task"), "r") as f:
text_format.Parse(f.read(), task)
options = task_utils.ParseOptions(task)
out_dir = os.path.join(FLAGS.out_dir, GetModelDir(options))
if not tf.gfile.IsDirectory(out_dir):
tf.gfile.MakeDirs(out_dir)
task_string = text_format.MessageToString(task)
print("\nWill evaluate task\n%s\n\n", task_string)
EvalTask(options, task_workdir, out_dir)
def AddGansAndDatasets():
"""Injects MultiGAN models, parameters and datasets.
This code injects the GAN model and its default parameters to the framework.
Must be run just after the main.
"""
gan_lib.MODELS.update({
"MultiGAN":
multi_gan.MultiGAN,
"MultiGANBackground":
multi_gan_background.MultiGANBackground
})
params.PARAMETERS.update({
"MultiGAN":
multi_gan.MultiGANHyperParams,
"MultiGANBackground":
multi_gan_background.MultiGANBackgroundHyperParams
})
eval_gan_lib.SUPPORTED_GANS.extend(["MultiGAN", "MultiGANBackground"])
eval_gan_lib.DEFAULT_VALUES.update({
"k": -1,
"aggregate": "none",
"embedding_dim": -1,
"n_blocks": -1,
"share_block_weights": False,
"n_heads": -1,
"background_interaction": False,
})
gan_lib.DATASETS.update(dataset.get_datasets())
params.DATASET_PARAMS.update(dataset.get_dataset_params())