reorganize code

add train.py and predict.py
move semi_sup, self_sup, noisy_label and weak_sup to net_run

Author: taigw

pymic/net_run/noisy_label/__init__.py

@@ -0,0 +1,8 @@
+from __future__ import absolute_import
+from pymic.net_run.noisy_label.nll_co_teaching import NLLCoTeaching
+from pymic.net_run.noisy_label.nll_trinet import NLLTriNet
+from pymic.net_run.noisy_label.nll_dast import NLLDAST
+
+NLLMethodDict = {'CoTeaching': NLLCoTeaching,
+    "TriNet": NLLTriNet,
+    "DAST": NLLDAST}

pymic/net_run_nll/nll_clslsr.py renamed to pymic/net_run/noisy_label/nll_clslsr.py

@@ -3,7 +3,7 @@
 import logging
 import os
 import sys
-import shutil
+from datetime import datetime
 from pymic.util.parse_config import *
 from pymic.net_run.agent_cls import ClassificationAgent
 from pymic.net_run.agent_seg import SegmentationAgent
@@ -12,34 +12,31 @@ def main():
     """
     The main function for running a network for training or inference.
     """
-    if(len(sys.argv) < 3):
-        print('Number of arguments should be 3. e.g.')
-        print('   pymic_run train config.cfg')
+    if(len(sys.argv) < 2):
+        print('Number of arguments should be 2. e.g.')
+        print('   pymic_test config.cfg')
         exit()
-    stage    = str(sys.argv[1])
-    cfg_file = str(sys.argv[2])
+    cfg_file = str(sys.argv[1])
     config   = parse_config(cfg_file)
     config   = synchronize_config(config)
-    log_dir  = config['training']['ckpt_save_dir']
+    log_dir  = config['testing']['output_dir']
     if(not os.path.exists(log_dir)):
         os.makedirs(log_dir, exist_ok=True)
-    if(stage == "train"):
-        dst_cfg = cfg_file if "/" not in cfg_file else cfg_file.split("/")[-1]
-        shutil.copy(cfg_file, log_dir + "/" + dst_cfg)
+
     if sys.version.startswith("3.9"):
-        logging.basicConfig(filename=log_dir+"/log_{0:}.txt".format(stage), level=logging.INFO,
-                            format='%(message)s', force=True) # for python 3.9
+        logging.basicConfig(filename=log_dir+"/log_test.txt", 
+                            level=logging.INFO, format='%(message)s', force=True) # for python 3.9
     else:
-        logging.basicConfig(filename=log_dir+"/log_{0:}.txt".format(stage), level=logging.INFO,
-                            format='%(message)s') # for python 3.6
+        logging.basicConfig(filename=log_dir+"/log_test.txt", 
+                            level=logging.INFO, format='%(message)s') # for python 3.6
     logging.getLogger().addHandler(logging.StreamHandler(sys.stdout))
     logging_config(config)
     task     = config['dataset']['task_type']
     assert task in ['cls', 'cls_nexcl', 'seg']
     if(task == 'cls' or task == 'cls_nexcl'):
-        agent = ClassificationAgent(config, stage)
+        agent = ClassificationAgent(config, 'test')
     else:
-        agent = SegmentationAgent(config, stage)
+        agent = SegmentationAgent(config, 'test')
     agent.run()
 
 if __name__ == "__main__":

pymic/net_run_nll/nll_co_teaching.py renamed to pymic/net_run/noisy_label/nll_co_teaching.py

@@ -0,0 +1,2 @@
+from __future__ import absolute_import
+from pymic.net_run.self_sup.self_sl_agent import SelfSLSegAgent

pymic/net_run_nll/nll_dast.py renamed to pymic/net_run/noisy_label/nll_dast.py

@@ -0,0 +1,16 @@
+from __future__ import absolute_import
+from pymic.net_run.semi_sup.ssl_abstract import SSLSegAgent
+from pymic.net_run.semi_sup.ssl_em import SSLEntropyMinimization
+from pymic.net_run.semi_sup.ssl_mt import SSLMeanTeacher
+from pymic.net_run.semi_sup.ssl_uamt import SSLUncertaintyAwareMeanTeacher
+from pymic.net_run.semi_sup.ssl_cct import SSLCCT
+from pymic.net_run.semi_sup.ssl_cps import SSLCPS
+from pymic.net_run.semi_sup.ssl_urpc import SSLURPC
+
+
+SSLMethodDict = {'EntropyMinimization': SSLEntropyMinimization,
+    'MeanTeacher': SSLMeanTeacher,
+    'UAMT': SSLUncertaintyAwareMeanTeacher,
+    'CCT': SSLCCT,
+    'CPS': SSLCPS,
+    'URPC': SSLURPC}