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# -*- coding: utf-8 -*-
# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
# holder of all proprietary rights on this computer program.
# You can only use this computer program if you have closed
# a license agreement with MPG or you get the right to use the computer
# program from someone who is authorized to grant you that right.
# Any use of the computer program without a valid license is prohibited and
# liable to prosecution.
#
# Copyright©2019 Max-Planck-Gesellschaft zur Förderung
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute
# for Intelligent Systems. All rights reserved.
#
# Contact: [email protected]
import argparse
import json
import os
import random
import string
from datetime import datetime
from yacs.config import CfgNode as CN
# Configuration variables
cfg = CN(new_allowed=True)
cfg.OUTPUT_DIR = 'results'
cfg.DEVICE = 'cuda'
cfg.DEBUG = False
cfg.LOGDIR = ''
cfg.VAL_VIS_BATCH_FREQ = 200
cfg.TRAIN_VIS_ITER_FERQ = 1000
cfg.SEED_VALUE = -1
cfg.TRAIN = CN(new_allowed=True)
cfg.LOSS = CN(new_allowed=True)
cfg.LOSS.KP_2D_W = 300.0
cfg.LOSS.KP_3D_W = 300.0
cfg.LOSS.SHAPE_W = 0.06
cfg.LOSS.POSE_W = 60.0
cfg.LOSS.VERT_W = 0.0
# Loss weights for dense correspondences
cfg.LOSS.INDEX_WEIGHTS = 2.0
# Loss weights for surface parts. (24 Parts)
cfg.LOSS.PART_WEIGHTS = 0.3
# Loss weights for UV regression.
cfg.LOSS.POINT_REGRESSION_WEIGHTS = 0.5
cfg.MODEL = CN(new_allowed=True)
cfg.MODEL.PyMAF = CN(new_allowed=True)
## switch
cfg.TRAIN.BATCH_SIZE = 64
cfg.TRAIN.VAL_LOOP = True
cfg.TEST = CN(new_allowed=True)
def get_cfg_defaults():
"""Get a yacs CfgNode object with default values for my_project."""
# Return a clone so that the defaults will not be altered
# This is for the "local variable" use pattern
# return cfg.clone()
return cfg
def update_cfg(cfg_file):
# cfg = get_cfg_defaults()
cfg.merge_from_file(cfg_file)
# return cfg.clone()
return cfg
def parse_args(args):
cfg_file = args.cfg_file
if args.cfg_file is not None:
cfg = update_cfg(args.cfg_file)
else:
cfg = get_cfg_defaults()
if args.misc is not None:
cfg.merge_from_list(args.misc)
return cfg
def parse_args_extend(args):
if args.resume:
if not os.path.exists(args.log_dir):
raise ValueError('Experiment are set to resume mode, but log directory does not exist.')
if args.cfg_file is not None:
cfg = update_cfg(args.cfg_file)
else:
cfg = get_cfg_defaults()
# load log's cfg
cfg_file = os.path.join(args.log_dir, 'cfg.yaml')
cfg = update_cfg(cfg_file)
if args.misc is not None:
cfg.merge_from_list(args.misc)
else:
parse_args(args)
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