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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) | |