def segment(folder, params):
'''
Segment all layers in a folder
'''
#create folders for the output
filelib.make_folders([
params.inputfolder + '../segmented/masks/glomeruli/' + folder,
params.inputfolder + '../segmented/masks/kidney/' + folder,
params.inputfolder + '../log/' + folder
])
start = time.time()
#list all files in the folder
files = filelib.list_image_files(params.inputfolder + folder)
files.sort()
params.folder = folder
#segment all layers in parallel
boost.run_parallel(process=segment_layer,
files=files,
params=params,
procname='Segmentation of glomeruli')
# segment_layer(files[50], params)
t = pd.Series({
'Segmentation': time.time() - start,
'threads': params.max_threads
})
t.to_csv(params.inputfolder + '../log/' + folder + 'Segmentation.csv',
sep='\t')
def segment(folder, params): ''' Segment all layers in a folder ''' #create folders for the output filelib.make_folders([params.inputfolder + '../segmented/outlines/' + folder, params.inputfolder + '../segmented/masks/' + folder]) #list all files in the folder files = filelib.list_image_files(params.inputfolder + folder) files.sort() ind = np.int_(np.arange(0, len(files), 10)) files = np.array(files)[ind] if not len(filelib.list_image_files(params.inputfolder + '../segmented/masks/' + folder)) == len(files): params.folder = folder #segment all layers in parallel boost.run_parallel(process = segment_layer, files = files, params = params, procname = 'Segmentation of glomeruli')
settingsfile = 'settings.csv'
params = pd.Series.from_csv(settingsfile, sep='\t')
#list folders with stacks to be analyzed
folders = list_subfolders(params.inputfolder, subfolders=[])
params.max_threads = 30
#segment each stack
for folder in folders:
segment(folder, params)
#label connected objects
params.max_threads = 25
boost.run_parallel(process=label_cells,
files=folders,
params=params,
procname='Labelling')
#quantify the segmented data
boost.run_parallel(process=quantify,
files=folders,
params=params,
procname='Quantification')
filelib.combine_statistics(
params.inputfolder + '../statistics/',
params.inputfolder + '../statistics/statistics_combined.csv')
compute_stack_stat(
params.inputfolder + '../statistics/statistics_combined.csv', params)
compute_size_distribution(
except: settingsfile = 'settings.csv' params = pd.Series.from_csv(settingsfile, sep = '\t') #list folders with stacks to be analyzed folders = list_subfolders(params.inputfolder, subfolders = []) #segment each stack for folder in folders: print folder segment(folder, params) #quantify the segmented data boost.run_parallel(process = quantify, files = folders, params = params, procname = 'Quantification') filelib.combine_statistics(params.inputfolder + '../statistics/', params.inputfolder + '../statistics_combined.csv')