from __future__ import print_function
import os
import torch
import argparse
from core.config import cfg
def add_global_arguments(parser):
parser.add_argument("--dataset", type=str,
help="Determines dataloader to use (only Pascal VOC supported)")
parser.add_argument("--exp", type=str, default="main",
help="ID of the experiment (multiple runs)")
parser.add_argument("--resume", type=str, default=None,
help="Snapshot \"ID,iter\" to load")
parser.add_argument("--run", type=str, help="ID of the run")
parser.add_argument('--workers', type=int, default=8,
metavar='N', help='dataloader threads')
parser.add_argument("--snapshot-dir", type=str, default='./snapshots',
help="Where to save snapshots of the model.")
parser.add_argument("--logdir", type=str, default='./logs',
help="Where to save log files of the model.")
parser.add_argument("--infer-list", type=str, default='data/val_augvoc.txt',
help="Path to a file list")
parser.add_argument("--mask-output-dir", type=str, default='results/',
help="Path where to save masks")
parser.add_argument('--world-size', default=8, type=int,
help='number of distributed processes')
parser.add_argument(
'--cfg', dest='cfg_file', required=True,
help='Config file for training (and optionally testing)')
parser.add_argument(
'--set', dest='set_cfgs',
help='Set config keys. Key value sequence seperate by whitespace.'
'e.g. [key] [value] [key] [value]',
default=[], nargs='+')
parser.add_argument("--random-seed", type=int, default=64, help="Random seed")
parser.add_argument("--local_rank", type=int, default=0, help="local_rank")
def maybe_create_dir(path):
if not os.path.exists(path):
os.makedirs(path)
def check_global_arguments(args):
torch.set_num_threads(args.workers)
if args.workers != torch.get_num_threads():
print("Warning: # of threads is only ", torch.get_num_threads())
setattr(args, "fixed_batch_path", os.path.join(args.logdir, args.dataset, args.exp, "fixed_batch.pt"))
args.logdir = os.path.join(args.logdir, args.dataset, args.exp, args.run)
maybe_create_dir(args.logdir)
args.snapshot_dir = os.path.join(args.snapshot_dir, args.dataset, args.exp, args.run)
maybe_create_dir(args.snapshot_dir)
def get_arguments(args_in):
"""Parse all the arguments provided from the CLI.
Returns:
A list of parsed arguments.
"""
parser = argparse.ArgumentParser(description="Model Evaluation")
add_global_arguments(parser)
args = parser.parse_args(args_in)
check_global_arguments(args)
return args