def main( ws_filename, label_filename, output_filename,
thr_low, thr_high, thr_inc,
calc_rfs=True, calc_re=True,
calc_vifs=True, calc_vi=True,
rel2d=False,
foreground_restriction=False,
split0=True,
other=None):
print("Reading data...")
ws_seg, dend_pairs, dend_values = io_utils.import_ws_file( ws_filename )
label_seg = io_utils.import_file( label_filename )
assert ws_seg.shape == label_seg.shape
thresholds = np.arange(thr_low, thr_high, thr_inc)
prep = utils.parse_fns( utils.prep_fns,
[rel2d, foreground_restriction] )
ws_seg, label_seg = utils.run_preprocessing( ws_seg, label_seg, prep )
om = utils.calc_overlap_matrix( ws_seg, label_seg, split0 )
metrics = utils.parse_fns( utils.metric_fns,
[calc_rfs,calc_re,
calc_vifs,calc_vi] )
results = init_results( metrics, len(thresholds) )
#descending threshold to allow incremental merging
for i in range(thresholds.size-1,-1,-1):
t = thresholds[i]
print("Threshold: {}".format(t))
start = timeit.default_timer()
om.merge_to_thr(dend_pairs, dend_values, t)
end = timeit.default_timer()
print("Mapping completed in {} seconds".format(end-start))
for (name, fn) in metrics:
(f,m,s) = fn(om, name, other)
results["{}/Full".format(name)][i] = f
results["{}/Merge".format(name)][i] = m
results["{}/Split".format(name)][i] = s
if len(results) > 0:
results["Thresholds"] = thresholds
io_utils.write_h5_map_file( results, output_filename )
def seg_metric( seg1, seg2, split0, *args ): '''High-level function which handles segmentations''' assert seg1.dtype == DTYPE assert seg2.dtype == DTYPE om = utils.calc_overlap_matrix(seg1, seg2, split0) om_metric_fn, metric_name = args[:2] score = om_metric(om_metric_fn, metric_name, om, *args[2:]) return score
def main(seg1_fname, seg2_fname,
calc_rand_score=True,
calc_rand_error=True,
calc_variation_score=True,
calc_variation_information=True,
relabel2d=False,
foreground_restricted=True,
split_0_segment=True,
other=None):
'''
Script functionality, computes the overlap matrix,
computes any specified metrics,
and prints the results nicely
'''
print("Loading Data...")
seg1 = io_utils.import_file(seg1_fname)
seg2 = io_utils.import_file(seg2_fname)
prep = utils.parse_fns( utils.prep_fns,
[relabel2d, foreground_restricted ] )
seg1, seg2 = utils.run_preprocessing( seg1, seg2, prep )
om = utils.calc_overlap_matrix(seg1, seg2, split_0_segment)
#Calculating each desired metric
metrics = utils.parse_fns( utils.metric_fns,
[calc_rand_score,
calc_rand_error,
calc_variation_score,
calc_variation_information] )
results = {}
for (name,metric_fn) in metrics:
if relabel2d:
full_name = "2D {}".format(name)
else:
full_name = name
(f,m,s) = metric_fn( om, full_name, other )
results["{} Full".format(name)] = f
results["{} Merge".format(name)] = m
results["{} Split".format(name)] = s
print("")
utils.print_metrics(results)
def main(ws_filename,
label_filename,
output_filename,
thr_low,
thr_high,
thr_inc,
calc_rfs=True,
calc_re=True,
calc_vifs=True,
calc_vi=True,
rel2d=False,
foreground_restriction=False,
split0=True,
other=None):
print("Reading data...")
ws_seg, dend_pairs, dend_values = io_utils.import_ws_file(ws_filename)
label_seg = io_utils.import_file(label_filename)
assert ws_seg.shape == label_seg.shape
thresholds = np.arange(thr_low, thr_high, thr_inc)
prep = utils.parse_fns(utils.prep_fns, [rel2d, foreground_restriction])
ws_seg, label_seg = utils.run_preprocessing(ws_seg, label_seg, prep)
om = utils.calc_overlap_matrix(ws_seg, label_seg, split0)
metrics = utils.parse_fns(utils.metric_fns,
[calc_rfs, calc_re, calc_vifs, calc_vi])
results = init_results(metrics, len(thresholds))
#descending threshold to allow incremental merging
for i in range(thresholds.size - 1, -1, -1):
t = thresholds[i]
print("Threshold: {}".format(t))
start = timeit.default_timer()
om.merge_to_thr(dend_pairs, dend_values, t)
end = timeit.default_timer()
print("Mapping completed in {} seconds".format(end - start))
for (name, fn) in metrics:
(f, m, s) = fn(om, name, other)
results["{}/Full".format(name)][i] = f
results["{}/Merge".format(name)][i] = m
results["{}/Split".format(name)][i] = s
if len(results) > 0:
results["Thresholds"] = thresholds
io_utils.write_h5_map_file(results, output_filename)
def main(
seg1_fname,
seg2_fname,
calc_rand_score=True,
calc_rand_error=True,
calc_variation_score=True,
calc_variation_information=True,
relabel2d=False,
foreground_restricted=True,
split_0_segment=True,
other=None,
):
"""
Script functionality, computes the overlap matrix,
computes any specified metrics,
and prints the results nicely
"""
print("Loading Data...")
seg1 = io_utils.import_file(seg1_fname)
seg2 = io_utils.import_file(seg2_fname)
prep = utils.parse_fns(utils.prep_fns, [relabel2d, foreground_restricted])
seg1, seg2 = utils.run_preprocessing(seg1, seg2, prep)
om = utils.calc_overlap_matrix(seg1, seg2, split_0_segment)
# Calculating each desired metric
metrics = utils.parse_fns(
utils.metric_fns, [calc_rand_score, calc_rand_error, calc_variation_score, calc_variation_information]
)
results = {}
for (name, metric_fn) in metrics:
if relabel2d:
full_name = "2D {}".format(name)
else:
full_name = name
(f, m, s) = metric_fn(om, full_name, other)
results["{} Full".format(name)] = f
results["{} Merge".format(name)] = m
results["{} Split".format(name)] = s
print("")
utils.print_metrics(results)