def eval_segment_with_annot(params, dict_annot, dict_segm, dict_label_hist=None,
name_csv=NAME_CSV_SEGM_STAT_SLIC_ANNOT, nb_jobs=1):
""" evaluate the segmentation results according given annotation
:param {str: ...} params:
:param {str: ndarray} dict_annot:
:param {str: ndarray} dict_segm:
:param {str: ndarray} dict_label_hist:
:param str name_csv:
:param int nb_jobs:
:return:
"""
if dict_label_hist is not None:
visu_histogram_labels(params, dict_label_hist)
assert sorted(dict_annot.keys()) == sorted(dict_segm.keys()), \
'mismatch in dictionary keys: \n%s \n%s' % (sorted(dict_annot.keys()),
sorted(dict_segm.keys()))
list_annot = [dict_annot[n] for n in dict_annot]
list_segm = [dict_segm[n] for n in dict_annot]
df_stat = seg_clf.compute_stat_per_image(list_segm, list_annot,
[n for n in dict_annot], nb_jobs)
path_csv = os.path.join(params['path_exp'], name_csv)
logging.info('STAT on seg_pipe and annot (%s):', name_csv)
df_stat.to_csv(path_csv)
logging.info(metrics.classification_report(
seg_label.convert_segms_2_list(list_segm),
seg_label.convert_segms_2_list(list_annot), digits=4))
logging.debug(repr(df_stat))
return df_stat
def eval_segment_with_annot(
params,
dict_annot,
dict_segm,
dict_label_hist=None,
name_csv='statistic___.csv',
drop_labels=None,
nb_workers=1,
):
""" evaluate the segmentation results according given annotation
:param dict params:
:param {str: ndarray} dict_annot:
:param {str: ndarray} dict_segm:
:param {str: ndarray} dict_label_hist:
:param str name_csv:
:param int nb_workers:
:return:
"""
if dict_label_hist is not None:
visu_histogram_labels(params, dict_label_hist)
if sorted(dict_annot) != sorted(dict_segm):
raise ValueError('mismatch in dictionary keys: \n%s \n%s' %
(sorted(dict_annot.keys()), sorted(dict_segm.keys())))
list_annot = [dict_annot[n] for n in dict_annot]
list_segm = [dict_segm[n] for n in dict_annot]
df_stat = seg_clf.compute_stat_per_image(list_segm,
list_annot,
list(dict_annot),
nb_workers,
drop_labels=drop_labels)
path_csv = os.path.join(params['path_exp'], name_csv)
logging.info('STATISTIC on segm and annot (%s):', name_csv)
df_stat.to_csv(path_csv)
logging.info(
metrics.classification_report(
seg_label.convert_segms_2_list(list_segm),
seg_label.convert_segms_2_list(list_annot),
digits=4))
logging.debug('%r', df_stat)
return df_stat