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)