Merge pull request #24 from HiLab-git/dev

Dev

pymic/net_run/agent_abstract.py

@@ -2,18 +2,11 @@
 from __future__ import print_function, division
 
 import os
-import time
 import random
 import torch
-import torchvision
 import numpy as np
-import torch.nn as nn
 import torch.optim as optim
-import torch.backends.cudnn as cudnn
-
 from abc import ABCMeta, abstractmethod
-from datetime import datetime
-from pymic.util.parse_config import parse_config
 from pymic.net_run.get_optimizer import get_optimiser
 
 def seed_torch(seed=1):

pymic/net_run/agent_cls.py

@@ -3,18 +3,11 @@
 
 import copy
 import csv
-import os
-import sys
 import time
-import random
 import torch
 from torchvision import transforms
 import numpy as np
 import torch.nn as nn
-import torch.optim as optim
-import torch.nn.functional as F
-import matplotlib.pyplot as plt
-from PIL import Image 
 from datetime import datetime
 from tensorboardX import SummaryWriter
 from pymic.io.nifty_dataset import ClassificationDataset

pymic/net_run/agent_seg.py

@@ -1,12 +1,8 @@
 # -*- coding: utf-8 -*-
 from __future__ import print_function, division
-from cmath import log
-
 import copy
 import os
-import sys
 import time
-import random
 import logging
 import scipy
 import torch
@@ -30,7 +26,6 @@
 from pymic.loss.seg.util import get_classwise_dice
 from pymic.transform.trans_dict import TransformDict
 from pymic.util.image_process import convert_label
-from pymic.util.parse_config import parse_config
 
 class SegmentationAgent(NetRunAgent):
     def __init__(self, config, stage = 'train'):

pymic/net_run/infer_func.py

@@ -1,11 +1,7 @@
 # -*- coding: utf-8 -*-
 from __future__ import print_function, division
 
-import os
-import sys
-import math
 import torch
-import numpy as np
 from torch.nn.functional import interpolate
 
 class Inferer(object):

setup.py

@@ -11,7 +11,7 @@
 
 setuptools.setup(
     name    = 'PYMIC',
-    version = "0.2.4",
+    version = "0.2.5",
     author  ='PyMIC Consortium',
     author_email = '[email protected]',
     description  = description,