neurofinder algorithm : local nmf

local-nmf.py

# neurofinder submission
# local nmf
#
# requirements:
# thunder-python v1.2.0
# thunder-extraction v1.1.0

import json
import thunder as td
from extraction import NMF

datasets = [
  '00.00.test','00.01.test','01.00.test',
  '01.01.test','02.00.test','02.01.test',
  '03.00.test','04.00.test','04.01.test'
]

submission = []

for dataset in datasets:
  print('processing dataset: %s' % dataset)
  print('loading')
  path = 'neurofinder.' + dataset
  data = td.images.fromtif(path + '/images', ext='tiff')
  print('analyzing')
  algorithm = NMF(k=5, percentile=99, max_iter=50, overlap=0.1)
  model = algorithm.fit(data, chunk_size=(50,50), padding=(25,25))
  merged = model.merge(0.1)
  print('found %g regions' % merged.regions.count)
  regions = [{'coordinates': region.coordinates.tolist()} for region in merged.regions]
  result = {'dataset': dataset, 'regions': regions}
  submission.append(result)

print('writing results')
with open('submission.json', 'w') as f:
  f.write(json.dumps(submission))