# Config # Config is used to set dataset path for training and testing ############################################################################## from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import torch from utils.attr_dict import AttrDict __C = AttrDict() cfg = __C __C.EPOCH = 0 # Use Class Uniform Sampling to give each class proper sampling __C.CLASS_UNIFORM_PCT = 0.0 # Use class weighted loss per batch to increase loss for low pixel count classes per batch __C.BATCH_WEIGHTING = False # Border Relaxation Count __C.BORDER_WINDOW = 1 # Number of epoch to use before turn off border restriction __C.REDUCE_BORDER_EPOCH = -1 # Comma Seperated List of class id to relax __C.STRICTBORDERCLASS = None #Attribute Dictionary for Dataset __C.DATASET = AttrDict()
""" ############################################################################## #Config ############################################################################## from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import torch from utils.attr_dict import AttrDict cfg = AttrDict() cfg.EPOCH = 0 # Use Class Uniform Sampling to give each class proper sampling cfg.CLASS_UNIFORM_PCT = 0.0 # Use class weighted loss per batch to increase loss for low pixel count classes per batch cfg.BATCH_WEIGHTING = False # Border Relaxation Count cfg.BORDER_WINDOW = 1 # Number of epoch to use before turn off border restriction cfg.REDUCE_BORDER_EPOCH = -1 # Comma Seperated List of class id to relax cfg.STRICTBORDERCLASS = None # Attribute Dictionary for Dataset cfg.DATASET = AttrDict()
