def main(_):
utils.set_gpus_to_use()
try:
import tensorvision.train
except ImportError:
logging.error("Could not import the submodules.")
logging.error("Please execute:"
"'git submodule update --init --recursive'")
exit(1)
with open(tf.app.flags.FLAGS.hypes, 'r') as f:
logging.info("f: %s", f)
hypes = json.load(f)
#utils.load_plugins()
if 'TV_DIR_RUNS' in os.environ:
os.environ['TV_DIR_RUNS'] = os.path.join(os.environ['TV_DIR_RUNS'],
'KittiBox')
utils.set_dirs(hypes, tf.app.flags.FLAGS.hypes)
utils._add_paths_to_sys(hypes)
logging.info("Initialize training folder")
train.initialize_training_folder(hypes)
#train.maybe_download_and_extract(hypes)
logging.info("Start training")
train.do_training(hypes)
def main():
with open('../config/fcn8_seg.json', 'r') as f:
logging.info("f: %s", f)
hypes = commentjson.load(f)
utils.set_dirs(hypes, '../config/fcn8_seg.json')
utils._add_paths_to_sys(hypes)
logging.info("Initialize training folder")
train.initialize_training_folder(hypes)
logging.info("Start training")
print('start')
train.do_training(hypes)
print('end')
def main(_):
utils.set_gpus_to_use()
sys.path.append("submodules/tensorflow-fcn")
sys.path.append("submodules/TensorVision")
import tensorvision.train
import tensorflow_fcn.utils
# try:
# import tensorvision.train
# import tensorflow_fcn.utils
# except ImportError:
# logging.error("Could not import the submodules.")
# logging.error("Please execute:"
# "'git submodule update --init --recursive'")
# exit(1)
if tf.app.flags.FLAGS.hypes is None:
logging.error("No hype file is given.")
logging.info("Usage: python train.py --hypes hypes/KittiClass.json")
exit(1)
with open(tf.app.flags.FLAGS.hypes, 'r') as f:
logging.info("f: %s", f)
hypes = commentjson.load(f)
utils.load_plugins()
if tf.app.flags.FLAGS.mod is not None:
import ast
mod_dict = ast.literal_eval(tf.app.flags.FLAGS.mod)
dict_merge(hypes, mod_dict)
if 'TV_DIR_RUNS' in os.environ:
os.environ['TV_DIR_RUNS'] = os.path.join(os.environ['TV_DIR_RUNS'],
'KittiSeg')
utils.set_dirs(hypes, tf.app.flags.FLAGS.hypes)
utils._add_paths_to_sys(hypes)
train.maybe_download_and_extract(hypes)
logging.info("Initialize training folder")
train.initialize_training_folder(hypes)
logging.info("Start training")
train.do_training(hypes)
def main(_):
utils.set_gpus_to_use()
try:
import tensorvision.train
import tensorflow_fcn.utils
except ImportError:
logging.error("Could not import the submodules.")
logging.error("Please execute:"
"'git submodule update --init --recursive'")
exit(1)
if tf.app.flags.FLAGS.hypes is None:
logging.error("No hype file is given.")
logging.info("Usage: python train.py --hypes hypes/KittiClass.json")
exit(1)
with open(tf.app.flags.FLAGS.hypes, 'r') as f:
logging.info("f: %s", f)
hypes = commentjson.load(f)
hypes['dist'] = FLAGS.dist
if FLAGS.layers:
hypes['arch']['layers'] = FLAGS.layers
if FLAGS.lr:
hypes['solver']['learning_rate'] = FLAGS.lr
if FLAGS.optimizer:
hypes['solver']['opt'] = FLAGS.optimizer
utils.load_plugins()
if tf.app.flags.FLAGS.mod is not None:
import ast
mod_dict = ast.literal_eval(tf.app.flags.FLAGS.mod)
dict_merge(hypes, mod_dict)
if 'TV_DIR_RUNS' in os.environ:
os.environ['TV_DIR_RUNS'] = os.path.join(os.environ['TV_DIR_RUNS'],
'KittiSeg')
utils.set_dirs(hypes, tf.app.flags.FLAGS.hypes)
utils._add_paths_to_sys(hypes)
train.maybe_download_and_extract(hypes)
logging.info("Initialize training folder")
train.initialize_training_folder(hypes)
train.do_training(hypes)
def main(_):
utils.set_gpus_to_use()
with open(tf.app.flags.FLAGS.hypes, 'r') as f:
logging.info("f: %s", f)
hypes = json.load(f)
utils.load_plugins()
if 'TV_DIR_RUNS' in os.environ:
os.environ['TV_DIR_RUNS'] = os.path.join(os.environ['TV_DIR_RUNS'],
'MediSeg')
utils.set_dirs(hypes, tf.app.flags.FLAGS.hypes)
utils._add_paths_to_sys(hypes)
logging.info("Initialize training folder")
train.initialize_training_folder(hypes)
train.maybe_download_and_extract(hypes)
logging.info("Start training")
train.do_training(hypes)
def main(_):
utils.set_gpus_to_use()
try:
import tensorvision.train
import tensorflow_fcn.utils
except ImportError:
logging.error("Could not import the submodules.")
logging.error("Please execute:"
"'git submodule update --init --recursive'")
exit(1)
if tf.app.flags.FLAGS.hypes is None:
logging.error("No hype file is given.")
logging.info("Usage: python train.py --hypes hypes/KittiClass.json")
exit(1)
with open(tf.app.flags.FLAGS.hypes, 'r') as f:
logging.info("f: %s", f)
hypes = commentjson.load(f)
utils.load_plugins()
if tf.app.flags.FLAGS.mod is not None:
import ast
mod_dict = ast.literal_eval(tf.app.flags.FLAGS.mod)
dict_merge(hypes, mod_dict)
os.environ["TV_DIR_DATA"] = "../../SemSeg_DATA/DATA"
os.environ["TV_DIR_RUNS"] = "../../SemSeg_DATA/RUNS"
# print(os.environ["TV_DIR_DATA"])
utils.set_dirs(hypes, tf.app.flags.FLAGS.hypes)
utils._add_paths_to_sys(hypes)
train.maybe_download_and_extract(hypes)
logging.info("Initialize training folder")
train.initialize_training_folder(hypes)
logging.info("Start training")
train.do_training(hypes)
def train_and_get_results(to_drop, hypes, encoder_path):
ga_content = {'encoder_name': 'fcn8_vgg',
'encoder_path': encoder_path,
'drop': to_drop}
with open(hypes['ga_data'], 'w') as f:
commentjson.dump(ga_content, f)
tf.reset_default_graph()
train.do_training(hypes)
# thanks to https://stackoverflow.com/questions/39327032/how-to-get-the-latest-file-in-a-folder-using-python
runs = glob.glob('RUNS/*')
latest_dir = max(runs, key=os.path.getctime)
log = os.path.join(latest_dir, 'output.log')
with open(log) as f:
lines = list(reversed(f.read().splitlines()))
duration = float(lines[1].split(':')[-1].strip())
ap = float(lines[2].split(':')[-1].strip())
maxf1 = float(lines[4].split(':')[-1].strip())
return duration, maxf1, ap
def main(_):
utils.set_gpus_to_use()
try:
import tensorvision.train
import tensorflow_fcn.utils
except ImportError:
logging.error("Could not import the submodules.")
logging.error("Please execute:"
"'git submodule update --init --recursive'")
exit(1)
if tf.app.flags.FLAGS.hypes is None:
logging.error("No hype file is given.")
logging.info("Usage: python train.py --hypes hypes/KittiClass.json")
exit(1)
with open(tf.app.flags.FLAGS.hypes, 'r') as f:
logging.info("f: %s", f)
hypes = commentjson.load(f)
utils.load_plugins()
if tf.app.flags.FLAGS.mod is not None:
import ast
mod_dict = ast.literal_eval(tf.app.flags.FLAGS.mod)
dict_merge(hypes, mod_dict)
if 'TV_DIR_RUNS' in os.environ:
os.environ['TV_DIR_RUNS'] = os.path.join(os.environ['TV_DIR_RUNS'],
'KittiSeg')
utils.set_dirs(hypes, tf.app.flags.FLAGS.hypes)
utils._add_paths_to_sys(hypes)
train.maybe_download_and_extract(hypes)
logging.info("Initialize training folder")
train.initialize_training_folder(hypes)
logging.info("Start training")
train.do_training(hypes)
def main(_):
logging.info(
"Initializing GPUs, plugins and creating the essential folders")
utils.set_gpus_to_use()
if FLAGS.hypes is None:
logging.error("No hypes are given.")
logging.error("Usage: python train.py --hypes hypes.json")
logging.error(" tf: tv-train --hypes hypes.json")
exit(1)
with open(FLAGS.hypes) as f:
logging.info("f: %s", f)
hypes = commentjson.load(f)
if FLAGS.mod is not None:
import ast
mod_dict = ast.literal_eval(FLAGS.mod)
dict_merge(hypes, mod_dict)
logging.info("Loading plugins")
utils.load_plugins()
logging.info("Set dirs")
utils.set_dirs(hypes, FLAGS.hypes)
logging.info("Add paths to sys")
utils._add_paths_to_sys(hypes)
logging.info("Initialize training folder")
train.initialize_training_folder(hypes)
tf.reset_default_graph()
logging.info("Start training")
train.do_training(hypes)
