def load_config(mode=None):
r"""loads model config
Args:
mode (int): 1: train, 2: test, 3: eval, reads from config file if not specified
"""
parser = argparse.ArgumentParser()
parser.add_argument('--path', '--checkpoints', type=str, default='./checkpoints', help='model checkpoints path (default: ./checkpoints)')
parser.add_argument('--model', type=int, choices=[1, 2, 3], help='1: edge model, 2: SR model, 3: joint SR model with edge enhancer')
#import pdb;pdb.set_trace()
# test mode
if mode == 2:
parser.add_argument('--input', type=str, help='path to the input images directory or an input image')
parser.add_argument('--output', type=str, help='path to the output directory')
args = parser.parse_args()
config_path = os.path.join(args.path, 'config.yml')
# create checkpoints path if does't exist
if not os.path.exists(args.path):
os.makedirs(args.path)
# copy config template if does't exist
if not os.path.exists(config_path):
copyfile('./config.yml', config_path)
# load config file
config = Config(config_path)
# train mode
if mode == 1:
config.MODE = 1
if args.model:
config.MODEL = args.model
# test mode
elif mode == 2:
config.MODE = 2
config.HR_SIZE = 0
config.MODEL = args.model if args.model is not None else 3
if args.input is not None:
config.TEST_FLIST_LR = args.input
if args.output is not None:
config.RESULTS = args.output
# eval mode
elif mode == 3:
config.MODE = 3
config.MODEL = args.model if args.model is not None else 3
return config
def load_config(mode=2):
config_path = os.path.join('./psv','config.yml')
# load config file
config = Config(config_path)
# test mode
if mode == 2:
config.MODE = 2
config.MODEL = 3
config.INPUT_SIZE = 0
#if args.input is not None:
config.TEST_FLIST = './Images'
#if args.mask is not None:
config.TEST_MASK_FLIST = './Masks'
#if args.output is not None:
config.RESULTS = './results'
return config
def load_config(mask_roi_path, image_roi_path, results_path, mode=None):
r"""loads model config
Args:
mode (int): 1: train, 2: test, 3: eval, reads from config file if not specified
"""
parser = argparse.ArgumentParser()
parser.add_argument('--path',
'--checkpoints',
type=str,
default='./checkpoints/places2',
help='model checkpoints path (default: ./checkpoints)')
parser.add_argument(
'--model',
type=int,
choices=[1, 2, 3, 4],
help=
'1: edge model, 2: inpaint model, 3: edge-inpaint model, 4: joint model'
)
# test mode
if mode == 2:
parser.add_argument(
'--input',
type=str,
default='./datasets/test/image_roi/',
help='path to the input images directory or an input image')
parser.add_argument('--mask',
type=str,
default='./datasets/test/mask_roi/',
help='path to the masks directory or a mask file')
parser.add_argument('--edge',
type=str,
help='path to the edges directory or an edge file')
parser.add_argument('--output',
type=str,
default='./results/',
help='path to the output directory')
args = parser.parse_args()
config_path = os.path.join(args.path, 'config.yml')
args.input = image_roi_path
args.mask = mask_roi_path
args.output = results_path
# create checkpoints path if does't exist
if not os.path.exists(args.path):
os.makedirs(args.path)
# copy config template if does't exist
if not os.path.exists(config_path):
copyfile('./config.yml.example', config_path)
# load config file
config = Config(config_path)
# train mode
if mode == 1:
config.MODE = 1
if args.model:
config.MODEL = args.model
# test mode
elif mode == 2:
config.MODE = 2
config.MODEL = args.model if args.model is not None else 3
config.INPUT_SIZE = 0
if args.input is not None:
config.TEST_FLIST = args.input
if args.mask is not None:
config.TEST_MASK_FLIST = args.mask
if args.edge is not None:
config.TEST_EDGE_FLIST = args.edge
if args.output is not None:
config.RESULTS = args.output
# eval mode
elif mode == 3:
config.MODE = 3
config.MODEL = args.model if args.model is not None else 3
return config
def load_config(mode=None):
r"""loads model config
"""
parser = argparse.ArgumentParser()
parser.add_argument('--path',
'--checkpoints',
type=str,
default='./checkpoints',
help='model checkpoints path (default: ./checkpoints)')
parser.add_argument(
'--model',
type=int,
choices=[1, 2, 3, 4],
help=
'1: edge model, 2: inpaint model, 3: edge-inpaint model, 4: joint model'
)
# test mode
parser.add_argument(
'--input',
type=str,
help='path to the input images directory or an input image')
parser.add_argument('--edge',
type=str,
help='path to the edges directory or an edge file')
parser.add_argument('--output',
type=str,
help='path to the output directory')
parser.add_argument('--remove',
nargs='*',
type=int,
help='objects to remove')
parser.add_argument('--cpu',
type=str,
help='machine to run segmentation model on')
args = parser.parse_args()
#if path for checkpoint not given
if args.path is None:
args.path = './checkpoints'
config_path = os.path.join(args.path, 'config.yml')
# create checkpoints path if does't exist
if not os.path.exists(args.path):
os.makedirs(args.path)
# copy config template if does't exist
if not os.path.exists(config_path):
copyfile('./config.yml.example', config_path)
# load config file
config = Config(config_path)
# test mode
config.MODE = 2
config.MODEL = args.model if args.model is not None else 3
config.OBJECTS = args.remove if args.remove is not None else [3, 15]
config.SEG_DEVICE = 'cpu' if args.cpu is not None else 'cuda'
config.INPUT_SIZE = 256
if args.input is not None:
config.TEST_FLIST = args.input
if args.edge is not None:
config.TEST_EDGE_FLIST = args.edge
if args.output is not None:
config.RESULTS = args.output
else:
if not os.path.exists('./results_images'):
os.makedirs('./results_images')
config.RESULTS = './results_images'
return config
def load_config(mode=None):
# ----------------------------------
# load model config
# mode(int): 1 train, 2 test, 3 eval
# ----------------------------------
parser = argparse.ArgumentParser()
parser.add_argument('--path', '--checkpoints', type=str, default='./checkpoints/place2',
help='model checkpoints path (default: ./checkpoints)')
parser.add_argument('--model', type=int, default=1, choices=[1, 2, 3, 4],
help='1: edge model, 2: inpaint model, 3: edge-inpaint model, 4: joint model')
# test mode
if mode == 2:
parser.add_argument('--input', type=str, help='path to the input images directory or an input image')
parser.add_argument('--mask', type=str, help='path to the masks directory or a mask file')
parser.add_argument('--edge', type=str, help='path to the edges directory or an edge file')
parser.add_argument('--output', type=str, help='path to the output directory')
args = parser.parse_args()
config_path = os.path.join(args.path, 'config.yml')
# create checkpoints path if does't exist
if not os.path.exists(args.path):
os.makedirs(args.path)
# copy config template if does't exist
if not os.path.exists(config_path):
# copyfile('./config.yml.example', config_path)
print('Copy config....')
copyfile('./config.yml', config_path)
print('End copy config...')
# load config file
config = Config(config_path)
# train mode
if mode == 1:
config.MODE = 1
if args.model:
config.MODEL = args.model
# test mode
elif mode == 2:
config.MODE = 2
config.MODEL = args.model if args.model is not None else 3
config.INPUT_SIZE = 0
if args.input is not None:
config.TEST_FLIST = args.input
if args.mask is not None:
config.TEST_MASK_FLIST = args.mask
if args.edge is not None:
config.TEST_EDGE_FLIST = args.edge
if args.output is not None:
config.RESULTS = args.output
# eval mode
elif mode == 3:
config.MODE = 3
config.MODEL = args.model if args.model is not None else 3
return config
def load_config(mode=None):
r"""loads model config
Args:
mode (int): 1: train, 2: test, 3: eval, reads from config file if not specified
"""
parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, default='./config/config.yml', help='model config file')
parser.add_argument('--model', type=int, choices=[1, 2, 3, 4], help='1: edge model, 2: inpaint model, 3: edge-inpaint model, 4: joint model')
# test mode
# TODO: update
if mode == 2:
parser.add_argument('--input', type=str, help='path to the input images directory or an input image')
parser.add_argument('--mask', type=str, help='path to the masks directory or a mask file')
parser.add_argument('--edge', type=str, help='path to the edges directory or an edge file')
parser.add_argument('--output', type=str, help='path to the output directory')
args = parser.parse_args()
# # copy config template if does't exist
# if not os.path.exists(config_path):
# copyfile('./config.yml.example', config_path)
# load config file
config = Config(args.config)
# train mode
if mode == 1:
# create checkpoints path if does't exist
if not os.path.exists(config.LOG_DIR):
os.makedirs(config.LOG_DIR)
if not os.path.exists(config.MODEL_DIR):
os.makedirs(config.MODEL_DIR)
config.MODE = 1
if args.model:
config.MODEL = args.model
# test mode
elif mode == 2:
config.MODE = 2
#config.MODEL = args.model if args.model is not None else 3
# Hack
config.INPUT_SIZE = 0
#
config._dict['WORD_BB_PERCENT_THRESHOLD'] = 0
config._dict['CHAR_BB_PERCENT_THRESHOLD'] = 0
config._dict['MASK_CORNER_OFFSET'] = 5
# TODO: update this part
if args.input is not None:
config.TEST_FLIST = args.input
if args.mask is not None:
config.TEST_MASK_FLIST = args.mask
if args.edge is not None:
config.TEST_EDGE_FLIST = args.edge
if args.output is not None:
config.RESULTS = args.output
# eval mode
elif mode == 3:
config.MODE = 3
config.MODEL = args.model if args.model is not None else 3
return config
def load_config(mode=None):
r"""loads model config
Args:
mode (int): 1: train, 2: test, 3: eval, reads from config file if not specified
"""
parser = argparse.ArgumentParser()
parser.add_argument('--path', '--checkpoints', type=str, default='./checkpoints', help='model checkpoints path (default: ./checkpoints)')
parser.add_argument('--model', type=int, choices=[1, 2, 3], help='1: landmark prediction model, 2: inpaint model, 3: joint model')
# test mode
if mode == 2:
parser.add_argument('--input', type=str, help='path to the input images directory or an input image')
parser.add_argument('--mask', type=str, help='path to the masks directory or a mask file')
parser.add_argument('--landmark', type=str, help='path to the landmarks directory or a landmark file')
parser.add_argument('--output', type=str, help='path to the output directory')
args = parser.parse_args()
config_path = os.path.join(args.path, 'config.yml')
# create checkpoints path if does't exist
if not os.path.exists(args.path):
os.makedirs(args.path)
# copy config template if does't exist
if not os.path.exists(config_path):
copyfile('./config.yml.example', config_path)
# load config file
config = Config(config_path)
# train mode
if mode == 1:
config.MODE = 1
if args.model:
config.MODEL = args.model
# test mode
elif mode == 2:
config.MODE = 2
config.MODEL = args.model if args.model is not None else 3
if args.input is not None:
config.TEST_INPAINT_IMAGE_FLIST = args.input
if args.mask is not None:
config.TEST_MASK_FLIST = args.mask
if args.landmark is not None:
config.TEST_INPAINT_LANDMARK_FLIST = args.landmark
if args.output is not None:
config.RESULTS = args.output
# eval mode
elif mode == 3:
config.MODE = 3
config.MODEL = args.model if args.model is not None else 3
return config
from torchFewShot.utils.torchtools import one_hot, adjust_learning_rate
sys.path.append('/home/lijunjie/edge-connect-master')
from shutil import copyfile
from src.config import Config
from src.edge_connect_few_shot import EdgeConnect
#config = load_config(mode)
config_path = os.path.join('/home/lijunjie/edge-connect-master/checkpoints/places2_authormodel', 'config.yml')
config = Config(config_path)
config.TEST_FLIST = '/home/lijunjie/edge-connect-master/examples/test_result/'
config.TEST_MASK_FLIST = '/home/lijunjie/edge-connect-master/examples/places2/masks'
config.RESULTS = './checkpoints/EC_test'
config.MODE = 2
if config.MODE == 2:
config.MODEL = 3
config.INPUT_SIZE = 0
config.mask_id=2
#if args.input is not None:
#config.TEST_FLIST = args.input
#if args.mask is not None:
#config.TEST_MASK_FLIST = args.mask
#if args.edge is not None:
#config.TEST_EDGE_FLIST = args.edge
#if args.output is not None:
#config.RESULTS = args.output
#exit(0)
def load_config(mode=None):
r"""loads model config
Args:
mode (int): 1: train, 2: test, 3: eval, reads from config file if not specified
"""
parser = argparse.ArgumentParser()
parser.add_argument('--path',
'--checkpoints',
type=str,
default='./checkpoints',
help='model checkpoints path (default: ./checkpoints)')
parser.add_argument(
'--model',
type=int,
choices=[1, 2, 3, 4],
help=
'1: edge model, 2: inpaint model, 3: edge-inpaint model, 4: joint model'
)
# test mode
if mode == 2:
parser.add_argument(
'--input',
type=str,
help='path to the input images directory or an input image')
parser.add_argument('--mask',
type=str,
help='path to the masks directory or a mask file')
parser.add_argument('--edge',
type=str,
help='path to the edges directory or an edge file')
parser.add_argument('--output',
type=str,
help='path to the output directory')
args = parser.parse_args()
config_path = os.path.join(args.path, 'config.yml')
# create checkpoints path if does't exist
if not os.path.exists(args.path):
os.makedirs(args.path)
# copy config template if does't exist
if not os.path.exists(config_path):
copyfile('./config.yml.example', config_path)
# load config file
config = Config(config_path)
# train mode
if mode == 1:
config.MODE = 1
if args.model:
config.MODEL = args.model
if config.SKIP_PHASE2 is None:
config.SKIP_PHASE2 = 0
if config.MODEL == 2 and config.SKIP_PHASE2 == 1:
raise Exception(
"MODEL is 2, cannot skip phase2! trun config.SKIP_PHASE2 off or just use MODEL 3."
)
# test mode
elif mode == 2:
config.MODE = 2
config.MODEL = args.model if args.model is not None else 3
config.INPUT_SIZE = 0
if args.input is not None:
config.TEST_FLIST = args.input
if args.mask is not None:
config.TEST_MASK_FLIST = args.mask
if args.edge is not None:
config.TEST_EDGE_FLIST = args.edge
if args.output is not None:
config.RESULTS = args.output
# eval mode
elif mode == 3:
config.MODE = 3
config.MODEL = args.model if args.model is not None else 3
return config
def load_config(mode=None):
r"""loads model config
Args:
mode (int): 1: train, 2: test, 3: eval, reads from config file if not specified
"""
parser = argparse.ArgumentParser()
parser.add_argument(
"--path",
"--checkpoints",
type=str,
default="./checkpoints",
help="model checkpoints path (default: ./checkpoints)",
)
parser.add_argument(
"--model",
type=int,
choices=[1, 2, 3, 4],
help="1: edge model, 2: inpaint model, 3: edge-inpaint model, 4: joint model",
)
# test mode
if mode == 2:
parser.add_argument("--input", type=str, help="path to the input images directory or an input image")
parser.add_argument("--mask", type=str, help="path to the masks directory or a mask file")
parser.add_argument("--edge", type=str, help="path to the edges directory or an edge file")
parser.add_argument("--output", type=str, help="path to the output directory")
args = parser.parse_args()
config_path = os.path.join(args.path, "config.yml")
# create checkpoints path if does't exist
if not os.path.exists(args.path):
os.makedirs(args.path)
# copy config template if does't exist
if not os.path.exists(config_path):
copyfile("./config.yml.example", config_path)
# load config file
config = Config(config_path)
# train mode
if mode == 1:
config.MODE = 1
if args.model:
config.MODEL = args.model
# test mode
elif mode == 2:
config.MODE = 2
config.MODEL = args.model if args.model is not None else 3
config.INPUT_SIZE = 0
if args.input is not None:
config.TEST_FLIST = args.input
if args.mask is not None:
config.TEST_MASK_FLIST = args.mask
if args.edge is not None:
config.TEST_EDGE_FLIST = args.edge
if args.output is not None:
config.RESULTS = args.output
# eval mode
elif mode == 3:
config.MODE = 3
config.MODEL = args.model if args.model is not None else 3
return config
def load_config(mode=None):
parser = argparse.ArgumentParser()
parser.add_argument("--path",
"--checkpoints",
type=str,
default="./checkpoints",
help="model checkpoint path, default = ./checkpoints")
parser.add_argument(
"--model",
type=int,
choices=[1, 2, 3],
help="1: edge model, 2: SR model, 3: joint SR model with edge enhancer"
)
parser.add_argument("--train_img_path", type=str, default="./train_images")
parser.add_argument("--test_img_path", type=str, default="./test_images")
parser.add_argument("--eval_img_path", type=str, default="./eval_images")
if mode == "test":
#parser.add_argument("--input", type = str, help = "path to a test image")
parser.add_argument("--output",
type=str,
help="path to a output folder")
args = parser.parse_args()
create_data_list(args.train_img_path, args.test_img_path,
args.eval_img_path, "./list_folder")
config_path = os.path.join(args.path, "config.yaml")
if not os.path.exists(args.path):
os.makedirs(args.path)
if not os.path.exists(config_path):
copyfile('./config.yaml', config_path)
config = Config(config_path)
#train mode
if mode == 1:
config.MODE = 1
if args.model:
config.MODEL = args.model
#test mode
elif mode == 2:
config.MODE = 2
config.HR_SIZE = 0
if args.model:
config.MODEL = args.model
else:
config.MODEL = 3
#eval mode
elif mode == 3:
config.MODE = 3
if args.model:
config.MODEL = args.model
else:
config.MODEL = 3
return config
