def testdata_chipmatch():
from ibeis.algo.hots import chip_match
# only the first indicies will matter in these test
# feature matches
fm_list = [
np.array([(0, 9), (1, 9), (2, 9), (3, 9)], dtype=np.int32),
np.array([(0, 9), (1, 9), (2, 9), (3, 9)], dtype=np.int32),
np.array([(0, 9), (1, 9), (2, 9), (3, 9)], dtype=np.int32),
np.array([(4, 9), (5, 9), (6, 9), (3, 9)], dtype=np.int32),
np.array([(0, 9), (1, 9), (2, 9), (3, 9), (4, 9)], dtype=np.int32)
]
# score each feature match as 1
fsv_list = [
np.array([(1,), (1,), (1,), (1,)], dtype=hstypes.FS_DTYPE),
np.array([(1,), (1,), (1,), (1,)], dtype=hstypes.FS_DTYPE),
np.array([(1,), (1,), (1,), (1,)], dtype=hstypes.FS_DTYPE),
np.array([(1,), (1,), (1,), (1,)], dtype=hstypes.FS_DTYPE),
np.array([(1,), (1,), (1,), (1,), (1, )], dtype=hstypes.FS_DTYPE),
]
cm = chip_match.ChipMatch(
qaid=1,
daid_list=np.array([1, 2, 3, 4, 5], dtype=np.int32),
fm_list=fm_list,
fsv_list=fsv_list,
dnid_list=np.array([1, 1, 2, 2, 3], dtype=np.int32),
fsv_col_lbls=['count'],
)
#print(cm.get_rawinfostr())
#if False:
# # DEBUG
# cm.rrr()
# print(cm.get_rawinfostr())
# print(cm.get_cvs_str(ibs=qreq_.ibs, numtop=None))
return cm
def testdata_chipmatch():
from ibeis.algo.hots import chip_match
# only the first indicies will matter in these test
# feature matches
fm_list = [
np.array([(0, 9), (1, 9), (2, 9), (3, 9)], dtype=np.int32),
np.array([(0, 9), (1, 9), (2, 9), (3, 9)], dtype=np.int32),
np.array([(0, 9), (1, 9), (2, 9), (3, 9)], dtype=np.int32),
np.array([(4, 9), (5, 9), (6, 9), (3, 9)], dtype=np.int32),
np.array([(0, 9), (1, 9), (2, 9), (3, 9), (4, 9)], dtype=np.int32)
]
# score each feature match as 1
fsv_list = [
np.array([(1, ), (1, ), (1, ), (1, )], dtype=hstypes.FS_DTYPE),
np.array([(1, ), (1, ), (1, ), (1, )], dtype=hstypes.FS_DTYPE),
np.array([(1, ), (1, ), (1, ), (1, )], dtype=hstypes.FS_DTYPE),
np.array([(1, ), (1, ), (1, ), (1, )], dtype=hstypes.FS_DTYPE),
np.array([(1, ), (1, ), (1, ), (1, ), (1, )], dtype=hstypes.FS_DTYPE),
]
cm = chip_match.ChipMatch(
qaid=1,
daid_list=np.array([1, 2, 3, 4, 5], dtype=np.int32),
fm_list=fm_list,
fsv_list=fsv_list,
dnid_list=np.array([1, 1, 2, 2, 3], dtype=np.int32),
fsv_col_lbls=['count'],
)
return cm
def make_empty_chip_matches(qreq_):
"""
returns empty query results for each external qaid
Returns:
list: cm_list
CommandLine:
python -m ibeis.algo.hots.query_request --exec-make_empty_chip_matches
Example:
>>> # ENABLE_DOCTEST
>>> from ibeis.algo.hots.query_request import * # NOQA
>>> import ibeis
>>> qreq_ = ibeis.main_helpers.testdata_qreq_()
>>> cm_list = qreq_.make_empty_chip_matches()
>>> cm = cm_list[0]
>>> cm.print_rawinfostr()
>>> result = ('cm_list = %s' % (str(cm_list),))
>>> print(result)
"""
external_qaids = qreq_.get_external_qaids()
#external_daids = qreq_.get_external_daids()
#external_dnids = qreq_.ibs.get_annot_name_rowids(external_daids)
# FIXME: hacky
cm_list = [
chip_match.ChipMatch(qaid, [], qnid=qreq_.ibs.get_annot_name_rowids(qaid))
for qaid in (external_qaids)
]
for cm in cm_list:
cm._empty_hack()
return cm_list
def match_single(smk, qaid, daids, qreq_, verbose=True):
"""
CommandLine:
python -m ibeis.algo.smk.smk_pipeline SMK.match_single --profile
python -m ibeis.algo.smk.smk_pipeline SMK.match_single --show
python -m ibeis SMK.match_single -a ctrl:qmingt=2 --profile --db PZ_Master1
python -m ibeis SMK.match_single -a ctrl --profile --db GZ_ALL
Example:
>>> # FUTURE_ENABLE
>>> from ibeis.algo.smk.smk_pipeline import * # NOQA
>>> import ibeis
>>> qreq_ = ibeis.testdata_qreq_(defaultdb='PZ_MTEST')
>>> ibs = qreq_.ibs
>>> daids = qreq_.daids
>>> #ibs, daids = ibeis.testdata_aids(defaultdb='PZ_MTEST', default_set='dcfg')
>>> qreq_ = SMKRequest(ibs, daids[0:1], daids, {'agg': True,
>>> 'num_words': 1000,
>>> 'sv_on': True})
>>> qreq_.ensure_data()
>>> qaid = qreq_.qaids[0]
>>> daids = qreq_.daids
>>> daid = daids[1]
>>> verbose = True
>>> cm = qreq_.smk.match_single(qaid, daids, qreq_)
>>> ut.quit_if_noshow()
>>> ut.qtensure()
>>> cm.ishow_analysis(qreq_)
>>> ut.show_if_requested()
"""
from ibeis.algo.hots import chip_match
from ibeis.algo.hots import pipeline
alpha = qreq_.qparams['smk_alpha']
thresh = qreq_.qparams['smk_thresh']
agg = qreq_.qparams['agg']
#nAnnotPerName = qreq_.qparams.nAnnotPerNameSVER
sv_on = qreq_.qparams.sv_on
if sv_on:
nNameShortList = qreq_.qparams.nNameShortlistSVER
shortsize = nNameShortList
else:
shortsize = None
X = qreq_.qinva.get_annot(qaid)
# Determine which database annotations need to be checked
#with ut.Timer('searching qaid=%r' % (qaid,), verbose=verbose):
hit_inva_wxs = ut.take(qreq_.dinva.wx_to_aids, X.wx_list)
hit_daids = np.array(list(set(ut.iflatten(hit_inva_wxs))))
# Mark impossible daids
#with ut.Timer('checking impossible daids=%r' % (qaid,), verbose=verbose):
valid_flags = check_can_match(qaid, hit_daids, qreq_)
valid_daids = hit_daids.compress(valid_flags)
shortlist = ut.Shortlist(shortsize)
#gammaX = smk.gamma(X, wx_to_weight, agg, alpha, thresh)
_prog = ut.ProgPartial(lbl='smk scoring qaid=%r' % (qaid, ),
enabled=verbose,
bs=True,
adjust=True)
wx_to_weight = qreq_.dinva.wx_to_weight
debug = False
if debug:
qnid = qreq_.get_qreq_annot_nids([qaid])[0]
daids = np.array(qreq_.daids)
dnids = qreq_.get_qreq_annot_nids(daids)
correct_aids = daids[np.where(dnids == qnid)[0]]
daid = correct_aids[0]
if agg:
for daid in _prog(valid_daids):
Y = qreq_.dinva.get_annot(daid)
item = match_kernel_agg(X, Y, wx_to_weight, alpha, thresh)
shortlist.insert(item)
else:
for daid in _prog(valid_daids):
Y = qreq_.dinva.get_annot(daid)
item = match_kernel_sep(X, Y, wx_to_weight, alpha, thresh)
shortlist.insert(item)
# Build chipmatches for the shortlist results
#with ut.Timer('build cms', verbose=verbose):
cm = chip_match.ChipMatch(qaid=qaid, fsv_col_lbls=['smk'])
cm.daid_list = []
cm.fm_list = []
cm.fsv_list = []
_prog = ut.ProgPartial(lbl='smk build cm qaid=%r' % (qaid, ),
enabled=verbose,
bs=True,
adjust=True)
for item in _prog(shortlist):
(score, score_list, Y, X_idx, Y_idx) = item
X_fxs = ut.take(X.fxs_list, X_idx)
Y_fxs = ut.take(Y.fxs_list, Y_idx)
# Only build matches for those that sver will use
if agg:
X_maws = ut.take(X.maws_list, X_idx)
Y_maws = ut.take(Y.maws_list, Y_idx)
fm, fs = smk_funcs.build_matches_agg(X_fxs, Y_fxs, X_maws,
Y_maws, score_list)
else:
fm, fs = smk_funcs.build_matches_sep(X_fxs, Y_fxs, score_list)
if len(fm) > 0:
#assert not np.any(np.isnan(fs))
daid = Y.aid
fsv = fs[:, None]
cm.daid_list.append(daid)
cm.fm_list.append(fm)
cm.fsv_list.append(fsv)
cm._update_daid_index()
cm.arraycast_self()
cm.score_name_maxcsum(qreq_)
#if False:
# cm.assert_self(qreq_=qreq_, verbose=True)
if sv_on:
cm = pipeline.sver_single_chipmatch(qreq_, cm, verbose=verbose)
cm.score_name_maxcsum(qreq_)
return cm