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cfg_net.txt
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[network1] # for detection
# type of network
net_type = PNet
# name of network
net_name = pnet
# input patch shape e.g, [D, H, W, C]
data_shape = [1, 96, 96, 1]
# output patch shape, [D, H, W, C]
label_shape = [1, 96, 96, 1]
# number of class
class_num = 2
# model_file
model_file = model/detect/pnet.ckpt
[network1_parameter]
[network2] # for segmentation
# type of network
net_type = PNet
# name of network
net_name = pnet_seg
# input patch shape e.g, [D, H, W, C]
data_shape = [1, 96, 96, 1]
# output patch shape, [D, H, W, C]
label_shape = [1, 96, 96, 1]
# number of class
class_num = 2
# model_file
model_file = model/segment/pnet_seg.ckpt
[network2_parameter]
[detect_testing]
fix_batch_size = False
use_depth_as_batch_size = True
# max batch size
batch_size = 80
resize_input = True
resize_input_to_given_shape_in_2d = [96, 96]
# 1, using fixed tensor shape (default), 2, adaptive censor shape in 2D, 3, adaptive censorship in 3D
shape_mode = 1
[segment_testing]
fix_batch_size = False
use_depth_as_batch_size = True
# max batch size
batch_size = 40
resize_input = True
resize_input_to_given_shape_in_2d = [96, 96]
# 1, using fixed tensor shape (default), 2, adaptive censor shape in 2D, 3, adaptive censorship in 3D
shape_mode = 1