reduced tensorflow log outputs

UnMicst.py

@@ -1,9 +1,13 @@
 import numpy as np
 from scipy import misc
+import os
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
+import logging
+logging.getLogger('tensorflow').setLevel(logging.FATAL)
 import tensorflow.compat.v1 as tf
 import shutil
 import scipy.io as sio
-import os, fnmatch, glob
+import fnmatch, glob
 import skimage.exposure as sk
 import skimage.io
 import argparse
@@ -590,7 +594,7 @@ def singleImageInference(image, mode, pmIndex):
 	parentFolder = os.path.dirname(os.path.dirname(imagePath))
 	fileName = os.path.basename(imagePath)
 	fileNamePrefix = fileName.split(os.extsep, 1)
-	print(fileName)
+	# print(fileName)
 	fileType = fileNamePrefix[1]
 
 	if fileType=='ome.tif' or fileType == 'btf' :
@@ -609,7 +613,7 @@ def singleImageInference(image, mode, pmIndex):
 		args.classOrder = range(nClass)
 
 	rawI = I
-	print(type(I))
+	# print(type(I))
 	hsize = int((float(I.shape[0]) * float(dsFactor)))
 	vsize = int((float(I.shape[1]) * float(dsFactor)))
 	I = resize(I, (hsize, vsize))

UnMicst1-5.py

@@ -1,11 +1,16 @@
 import numpy as np
 from scipy import misc
+import os
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
+import logging
+logging.getLogger('tensorflow').setLevel(logging.FATAL)
+
 import tensorflow.compat.v1 as tf
 from tensorflow import keras
 from tensorflow.keras import layers
 import shutil
 import scipy.io as sio
-import os, fnmatch, glob
+import fnmatch, glob
 import skimage.exposure as sk
 import skimage.io
 import argparse
@@ -764,7 +769,7 @@ def singleImageInference(image, mode, pmIndex):
 	parentFolder = os.path.dirname(os.path.dirname(imagePath))
 	fileName = os.path.basename(imagePath)
 	fileNamePrefix = fileName.split(os.extsep, 1)
-	print(fileName)
+	# print(fileName)
 	fileType = fileNamePrefix[1]
 
 	if fileType == 'ome.tif' or fileType == 'btf':

UnMicst2.py

@@ -1,11 +1,16 @@
 import numpy as np
 from scipy import misc
+import os
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
+import logging
+logging.getLogger('tensorflow').setLevel(logging.FATAL)
+
 import tensorflow.compat.v1 as tf
 from tensorflow import keras
 from tensorflow.keras import layers
 import shutil
 import scipy.io as sio
-import os, fnmatch, glob
+import fnmatch, glob
 import skimage.exposure as sk
 import skimage.io
 import argparse
@@ -742,7 +747,7 @@ def singleImageInference(image, mode, pmIndex):
     parentFolder = os.path.dirname(os.path.dirname(imagePath))
     fileName = os.path.basename(imagePath)
     fileNamePrefix = fileName.split(os.extsep, 1)
-    print(fileName)
+    # print(fileName)
     fileType = fileNamePrefix[1]
 
     for iChan in range(len(channel)):

unmicstWrapper.py

@@ -23,6 +23,7 @@
 
     scriptPath =os.path.dirname(os.path.realpath(__file__))
 
+
 cmd="python " + scriptPath + os.sep
 
 channel = args.channel
@@ -36,16 +37,19 @@
 elif args.tool == 'UnMicst':
     cmd = cmd + "UnMicst.py "
     channel = str(channel[0])
-    print("WARNING! YOU HAVE OPTED TO USE UNMICST V1, WHICH IS GETTING TIRED AND OLD. CONSIDERING USING V1.5 OR V2(IF YOU ALSO HAVE A NUCLEAR ENVELOPE STAIN")
+    print('')
+    print("WARNING! YOU HAVE OPTED TO USE UNMICST V1, WHICH IS GETTING TIRED AND OLD. CONSIDER USING V1.5 OR V2(IF YOU ALSO HAVE A NUCLEAR ENVELOPE STAIN")
+    print('')
 elif args.tool == 'UnMicstCyto2':
     cmd = cmd + "UnMicstCyto2.py "
     channel = str(channel[0])
 else:
     cmd = cmd + "UnMicst1-5.py "
     channel = str(channel[0])
+    print('')
     print(
         "WARNING! USING V1.5 AS DEFAULT. THIS MODEL HAS BEEN TRAINED ON MORE TISSUE TYPES. IF YOU WANT V1, USE --tool UnMicst")
-
+    print('')
 
 cmd = cmd + " " + args.imagePath
 cmd = cmd + " --channel " + str(channel)