Merge branch 'master' of github.com:JamesEMcClure/LBPM-WIA

workflows/SegmentingImage/SegmentMicromodelTiff_Group.py

@@ -4,50 +4,53 @@ import numpy as np
 import matplotlib.pylab as plt
 from glob import glob
 from PIL import Image # import Python Imaging Library (PIL)
-import os
 import sys
-
-basename=sys.argv[1]
-plt.rcParams["savefig.directory"] = os.getcwd() # change the default pylab 'savefig' path (i.e. ~/) to cwd
 from SegmentMicromodelTiff_utils import convert_image_to_array,read_input_parameters
 
-# Load a group of *.in files 
+# Check if there is a proper command line argument
-# e.g. 'parameters_1.in' etc.
+if len(sys.argv) !=2:
-file_input_group = glob('Micromodel.in')
+    sys.stderr.write('Usage: ' + sys.argv[0] + ' <Input parameter file>\n')
-#output_result = np.empty((0,),dtype=float)
+    sys.exit()
+# end if
 
+input_parameter_file = sys.argv[1] # Give the name of the input parameter file 
+base_name_output = '_segmented.raw'# The string will be appended at the end of the 
+                                   # name of the input image as an output file name
+image_format = '.tiff' # format of experimental images
 
+# Read other input parameters
+Para = read_input_parameters(input_parameter_file)
+imin = Para['imin']
+imax = Para['imax']
+imin_b = Para['imin_b'] # greater than 'imin'
+imax_b = Para['imax_b'] # smaller than 'imax'
+top_layer = Para['top_layer']
+bot_layer = Para['bot_layer']
+DEPTH = Para['DEPTH']
+NY = imax - imin
+NZ = NY
+NX = DEPTH+top_layer+bot_layer
+
+# parameters for segmentation
+threshold_nw = Para['threshold_nw'] # NW phase: RGB values > threshold_nw
+threshold_s  = Para['threshold_s']  # solid:    RGB values < threshold_s
+# W phase: threshold_s <= RGB values <= threshold_nw
+
+# Load a group of image files with 'base_name' in the names of files 
+# e.g. 'Micromodel_1.tiff' etc.
+file_input_group = glob('*'+Para['base_name']+'*'+image_format) # need to match the image format
+
+# Process all imported experimental images
 if not file_input_group:
     print 'Error: Input files cannot be found ! '
 else:
     for ii in range(len(file_input_group)):
         file_input_single = file_input_group[ii]
-        Para = read_input_parameters(file_input_single)
+        print "Processing image "+file_input_single+" now..."
-        # set your output file names
-        input_file_idx = file_input_single[file_input_single.find('parameters_')+len('parameters_'):file_input_single.find('.in')]
-        output_file_name = 'Segmented_image_test_'+input_file_idx+'.raw'
-
-        imin = Para['imin']
-        imax = Para['imax']
-        imin_b = Para['imin_b'] # greater than 'imin'
-        imax_b = Para['imax_b'] # smaller than 'imax'
-        top_layer = Para['top_layer']
-        bot_layer = Para['bot_layer']
-        DEPTH = Para['DEPTH']
-        NY = imax - imin
-        NZ = NY
-        NX = DEPTH+top_layer+bot_layer
-
-        print "Processing "+Para['image_file_name']+" now..."
         print "------ Micromodel dimensions (NX, NY, NZ) are (%i, %i, %i) ------" % (NX,NY,NZ)
         
-        # parameters for segmentation
-        threshold_nw = Para['threshold_nw'] # NW phase: RGB values > threshold_nw
-        threshold_s  = Para['threshold_s']  # solid:    RGB values < threshold_s
-        # W phase: threshold_s <= RGB values <= threshold_nw
-
         # Get an array from the input .tiff image
-        im_array = convert_image_to_array(Para['image_file_name'],imin,imax)
+        im_array = convert_image_to_array(file_input_single,imin,imax)
 
         # Initialize the segmented image 'ID'
         # NOTE: 'ID' has the dimension (height, width, DEPTH)
@@ -65,8 +68,10 @@ else:
         # Calculate the porosity
         POROSITY = 1.0 - 1.0*ID[ID==0].size/ID.size
         print "Porosity of the micromodel is: "+str(POROSITY) 
-
+        
-
+        # Write the segmeted data to the output
+        # set the output file names (need to chop off say the '.tiff' part)
+        output_file_name = file_input_single[:file_input_single.find('.')]+base_name_output
         # Write out the segmented data (in binary format)
         print "The segmented image is written to "+output_file_name+" now..."
         ID.tofile(output_file_name)
@@ -79,20 +84,20 @@ else:
 
     
 # In case you want to test the segmentation
-plt.figure(1)
+#plt.figure(1)
 #plt.subplot(1,2,1)
 #plt.title('original RGB figure')    
 #plt.pcolormesh(im_array);
 #plt.axis('equal')
 #plt.colorbar()
 #plt.subplot(1,2,2)
-plt.title('Segmented image')
+#plt.title('Segmented image')
 # This will show the last-processed segmented image
-cmap = plt.cm.get_cmap('hot',3) #Plot 3 discrete colors for NW, W and Solids
+#cmap = plt.cm.get_cmap('hot',3) #Plot 3 discrete colors for NW, W and Solids
-cax=plt.pcolormesh(ID[:,:,NX/2],cmap=cmap,vmin=-0.5,vmax=2.5);
+#cax=plt.pcolormesh(ID[:,:,NX/2],cmap=cmap,vmin=-0.5,vmax=2.5);
-cbar = plt.colorbar(cax,ticks=[0,1,2])
+#cbar = plt.colorbar(cax,ticks=[0,1,2])
-plt.axis('equal')
+#plt.axis('equal')
-plt.show()
+#plt.show()
 
 
 

workflows/SegmentingImage/SegmentMicromodelTiff_utils.py

@@ -21,7 +21,7 @@ def convert_image_to_array(file_name,imin,imax):
 def read_input_parameters(input_file_name):
     # input_file_name is a string
     # The *.in file has the following lines
-    # line 0: the name of the image file e.g. *.tiff
+    # line 0: the base name of the experimental images
     # line 1: imin imax
     # line 2: imin_b imax_b
     # line 3: top_layer bottom_layer DEPTH
@@ -30,7 +30,7 @@ def read_input_parameters(input_file_name):
     #        'threshold_s'  means: solid:    RGB values < threshold_s
     f = open(input_file_name,'r') # read-only
     lines = f.readlines()
-    output_file = {'image_file_name':lines[0].splitlines()[0]}
+    output_file = {'base_name':lines[0].splitlines()[0]}
     line1_array = np.fromstring(lines[1].splitlines()[0],dtype=np.int32,sep=' ')
     line2_array = np.fromstring(lines[2].splitlines()[0],dtype=np.int32,sep=' ')
     line3_array = np.fromstring(lines[3].splitlines()[0],dtype=np.int32,sep=' ')