# Factor for reducing the learning rate
__C.TRAIN.GAMMA = 0.1
# Whether to double the learning rate for bias
__C.TRAIN.DOUBLE_BIAS = True
# Whether to initialize the weights with truncated normal distribution
__C.TRAIN.TRUNCATED = False
# Whether to have weight decay on bias as well
__C.TRAIN.BIAS_DECAY = False
##### RPN OPTION ####
__C.ANCHOR_SCALES = np.array([8, 16, 32])
__C.ANCHOR_RATIOS = [0.5, 1, 2]
# Down-sampling ratio
__C.FEAT_STRIDE = [
16,
]
__C.TRAIN.RPN_CLOBBER_POSITIVES = False
__C.TRAIN.RPN_POSITIVE_OVERLAP = 0.7
__C.TRAIN.RPN_NEGATIVE_OVERLAP = 0.3
__C.TRAIN.RPN_BATCHSIZE = 256
__C.TRAIN.RPN_FG_FRACTION = 0.5
