def load_gztest(ibs):
r"""
CommandLine:
python -m ibeis.algo.hots.special_query --test-load_gztest
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.algo.hots.devcases import * # NOQA
>>> import ibeis
>>> ibs = ibeis.opendb('GZ_ALL')
"""
from os.path import join
from ibeis.algo.hots import match_chips4 as mc4
dir_ = ut.get_module_dir(mc4)
eval_text = ut.read_from(join(dir_, 'GZ_TESTTUP.txt'))
testcases = eval(eval_text)
count_dict = ut.count_dict_vals(testcases)
print(ut.dict_str(count_dict))
testtup_list = ut.flatten(
ut.dict_take_list(testcases, [
'vsone_wins', 'vsmany_outperformed', 'vsmany_dominates',
'vsmany_wins'
]))
qaid_list = [testtup.qaid_t for testtup in testtup_list]
visual_uuids = ibs.get_annot_visual_uuids(qaid_list)
visual_uuids
def load_gztest(ibs):
r"""
CommandLine:
python -m ibeis.algo.hots.special_query --test-load_gztest
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.algo.hots.devcases import * # NOQA
>>> import ibeis
>>> ibs = ibeis.opendb('GZ_ALL')
"""
from os.path import join
from ibeis.algo.hots import match_chips4 as mc4
dir_ = ut.get_module_dir(mc4)
eval_text = ut.read_from(join(dir_, 'GZ_TESTTUP.txt'))
testcases = eval(eval_text)
count_dict = ut.count_dict_vals(testcases)
print(ut.dict_str(count_dict))
testtup_list = ut.flatten(ut.dict_take_list(testcases, ['vsone_wins',
'vsmany_outperformed',
'vsmany_dominates',
'vsmany_wins']))
qaid_list = [testtup.qaid_t for testtup in testtup_list]
visual_uuids = ibs.get_annot_visual_uuids(qaid_list)
visual_uuids
def check_results(ibs_gt, ibs2, aid1_to_aid2, aids_list1_, incinfo):
"""
reports how well the incremental query ran when the oracle was calling the
shots.
"""
print('--------- CHECKING RESULTS ------------')
testcases = incinfo.get('testcases')
if testcases is not None:
count_dict = ut.count_dict_vals(testcases)
print('+--')
#print(ut.dict_str(testcases))
print('---')
print(ut.dict_str(count_dict))
print('L__')
# TODO: dont include initially added aids in the result reporting
aid_list1 = aids_list1_ # ibs_gt.get_valid_aids()
#aid_list1 = ibs_gt.get_aids_with_groundtruth()
aid_list2 = ibs2.get_valid_aids()
nid_list1 = ibs_gt.get_annot_nids(aid_list1)
nid_list2 = ibs2.get_annot_nids(aid_list2)
# Group annotations from test and gt database by their respective names
grouped_dict1 = ut.group_items(aid_list1, nid_list1)
grouped_dict2 = ut.group_items(aid_list2, nid_list2)
grouped_aids1 = list(six.itervalues(grouped_dict1))
grouped_aids2 = list(map(tuple, six.itervalues(grouped_dict2)))
#group_nids1 = list(six.iterkeys(grouped_dict1))
#group_nids2 = list(six.iterkeys(grouped_dict2))
# Transform annotation ids from database1 space to database2 space
grouped_aids1_t = [
tuple(ut.dict_take_list(aid1_to_aid2, aids1))
for aids1 in grouped_aids1
]
set_grouped_aids1_t = set(grouped_aids1_t)
set_grouped_aids2 = set(grouped_aids2)
# Find names we got right. (correct groupings of annotations)
# these are the annotation groups that are intersecting between
# the test database and groundtruth database
perfect_groups = set_grouped_aids2.intersection(set_grouped_aids1_t)
# Find names we got wrong. (incorrect groupings of annotations)
# The test database sets that were not perfect
nonperfect_groups = set_grouped_aids2.difference(perfect_groups)
# What we should have got
# The ground truth database sets that were not fully identified
missed_groups = set_grouped_aids1_t.difference(perfect_groups)
# Mark non perfect groups by their error type
false_negative_groups = [] # failed to link enough
false_positive_groups = [] # linked too much
for nonperfect_group in nonperfect_groups:
if ut.is_subset_of_any(nonperfect_group, missed_groups):
false_negative_groups.append(nonperfect_group)
else:
false_positive_groups.append(nonperfect_group)
# Get some more info on the nonperfect groups
# find which groups should have been linked
aid2_to_aid1 = ut.invert_dict(aid1_to_aid2)
false_negative_groups_t = [
tuple(ut.dict_take_list(aid2_to_aid1, aids2))
for aids2 in false_negative_groups
]
false_negative_group_nids_t = ibs_gt.unflat_map(ibs_gt.get_annot_nids,
false_negative_groups_t)
assert all(map(ut.allsame,
false_negative_group_nids_t)), 'inconsistent nids'
false_negative_group_nid_t = ut.get_list_column(
false_negative_group_nids_t, 0)
# These are the links that should have been made
missed_links = ut.group_items(false_negative_groups,
false_negative_group_nid_t)
print(ut.dict_str(missed_links))
print('# Name with failed links (FN) = %r' % len(false_negative_groups))
print('... should have reduced to %d names.' % (len(missed_links)))
print('# Name with wrong links (FP) = %r' % len(false_positive_groups))
print('# Name correct names (TP) = %r' % len(perfect_groups))
elif vsmany_rank is not None and vsone_rank is None:
if vsmany_rank < 5:
append_case(VSMANY_DOMINATES, testtup)
else:
append_case(VSMANY_OUTPERFORMED, testtup)
elif vsmany_rank is None:
append_case(BOTH_FAIL, testtup)
elif vsone_rank > vsmany_rank:
append_case(VSMANY_WINS, testtup)
elif vsone_rank < vsmany_rank:
append_case(VSONE_WINS, testtup)
elif vsone_rank == vsmany_rank:
append_case(WASH, testtup)
else:
raise AssertionError('unenumerated case')
count_dict = ut.count_dict_vals(testcases)
print('+--')
#print(ut.dict_str(testcases))
print('---')
print(ut.dict_str(count_dict))
print('L__')
#ut.embed()
@profile
def query_vsmany_initial(ibs,
qaids,
daids,
use_cache=False,
qreq_vsmany_=None,
save_qcache=False):
def check_results(ibs_gt, ibs2, aid1_to_aid2, aids_list1_, incinfo):
"""
reports how well the incremental query ran when the oracle was calling the
shots.
"""
print('--------- CHECKING RESULTS ------------')
testcases = incinfo.get('testcases')
if testcases is not None:
count_dict = ut.count_dict_vals(testcases)
print('+--')
#print(ut.dict_str(testcases))
print('---')
print(ut.dict_str(count_dict))
print('L__')
# TODO: dont include initially added aids in the result reporting
aid_list1 = aids_list1_ # ibs_gt.get_valid_aids()
#aid_list1 = ibs_gt.get_aids_with_groundtruth()
aid_list2 = ibs2.get_valid_aids()
nid_list1 = ibs_gt.get_annot_nids(aid_list1)
nid_list2 = ibs2.get_annot_nids(aid_list2)
# Group annotations from test and gt database by their respective names
grouped_dict1 = ut.group_items(aid_list1, nid_list1)
grouped_dict2 = ut.group_items(aid_list2, nid_list2)
grouped_aids1 = list(six.itervalues(grouped_dict1))
grouped_aids2 = list(map(tuple, six.itervalues(grouped_dict2)))
#group_nids1 = list(six.iterkeys(grouped_dict1))
#group_nids2 = list(six.iterkeys(grouped_dict2))
# Transform annotation ids from database1 space to database2 space
grouped_aids1_t = [tuple(ut.dict_take_list(aid1_to_aid2, aids1)) for aids1 in grouped_aids1]
set_grouped_aids1_t = set(grouped_aids1_t)
set_grouped_aids2 = set(grouped_aids2)
# Find names we got right. (correct groupings of annotations)
# these are the annotation groups that are intersecting between
# the test database and groundtruth database
perfect_groups = set_grouped_aids2.intersection(set_grouped_aids1_t)
# Find names we got wrong. (incorrect groupings of annotations)
# The test database sets that were not perfect
nonperfect_groups = set_grouped_aids2.difference(perfect_groups)
# What we should have got
# The ground truth database sets that were not fully identified
missed_groups = set_grouped_aids1_t.difference(perfect_groups)
# Mark non perfect groups by their error type
false_negative_groups = [] # failed to link enough
false_positive_groups = [] # linked too much
for nonperfect_group in nonperfect_groups:
if ut.is_subset_of_any(nonperfect_group, missed_groups):
false_negative_groups.append(nonperfect_group)
else:
false_positive_groups.append(nonperfect_group)
# Get some more info on the nonperfect groups
# find which groups should have been linked
aid2_to_aid1 = ut.invert_dict(aid1_to_aid2)
false_negative_groups_t = [tuple(ut.dict_take_list(aid2_to_aid1, aids2)) for aids2 in false_negative_groups]
false_negative_group_nids_t = ibs_gt.unflat_map(ibs_gt.get_annot_nids, false_negative_groups_t)
assert all(map(ut.allsame, false_negative_group_nids_t)), 'inconsistent nids'
false_negative_group_nid_t = ut.get_list_column(false_negative_group_nids_t, 0)
# These are the links that should have been made
missed_links = ut.group_items(false_negative_groups, false_negative_group_nid_t)
print(ut.dict_str(missed_links))
print('# Name with failed links (FN) = %r' % len(false_negative_groups))
print('... should have reduced to %d names.' % (len(missed_links)))
print('# Name with wrong links (FP) = %r' % len(false_positive_groups))
print('# Name correct names (TP) = %r' % len(perfect_groups))
def test_vsone_errors(ibs, daids, qaid2_qres_vsmany, qaid2_qres_vsone, incinfo):
"""
ibs1 = ibs_gt
ibs2 = ibs (the current test database, sorry for the backwardness)
aid1_to_aid2 - maps annots from ibs1 to ibs2
"""
WASH = 'wash'
BOTH_FAIL = 'both_fail'
SINGLETON = 'singleton'
VSMANY_OUTPERFORMED = 'vsmany_outperformed'
VSMANY_DOMINATES = 'vsmany_dominates'
VSMANY_WINS = 'vsmany_wins'
VSONE_WINS = 'vsone_wins'
if 'testcases' not in incinfo:
testcases = {}
for case in [WASH, BOTH_FAIL, SINGLETON, VSMANY_OUTPERFORMED,
VSMANY_DOMINATES, VSMANY_WINS, VSONE_WINS]:
testcases[case] = []
incinfo['testcases'] = testcases
testcases = incinfo['testcases']
def append_case(case, testtup):
print('APPENDED NEW TESTCASE: case=%r' % (case,))
print('* testup = %r' % (testtup,))
print('* vuuid = %r' % (ibs_gt.get_annot_visual_uuids(testtup.qaid_t),))
if ut.get_argflag('--interupt-case') and case in [VSMANY_WINS, VSMANY_DOMINATES]:
incinfo['interactive'] = True
incinfo['use_oracle'] = False
incinfo['STOP'] = True
if ut.is_developer():
import plottool as pt # NOQA
IPYTHON_COMMANDS = """
>>> %pylab qt4
>>> from ibeis.viz.interact import interact_matches # NOQA
>>> #qres_vsmany = ut.search_stack_for_localvar('qres_vsmany')
>>> ibs = ut.search_stack_for_localvar('ibs')
>>> daids = ut.search_stack_for_localvar('daids')
>>> qnid_t = ut.search_stack_for_localvar('qnid_t')
>>> qres_vsone = ut.search_stack_for_localvar('qres_vsone')
>>> all_nids_t = ut.search_stack_for_localvar('all_nids_t')
>>> # Find index in daids of correct matches
>>> cm = qres_vsone
>>> correct_indices = np.where(np.array(all_nids_t) == qnid_t)[0]
>>> correct_aids2 = ut.take(daids, correct_indices)
>>> qaid = cm.qaid
>>> aid = correct_aids2[0]
>>> # Report visual uuid for inclusion or exclusion in script
>>> print(ibs.get_annot_visual_uuids([qaid, aid]))
>>> # Feature match things
>>> print('cm.filtkey_list = %r' % (cm.filtkey_list,))
>>> fm = cm.aid2_fm[aid]
>>> fs = cm.aid2_fs[aid]
>>> fsv = cm.aid2_fsv[aid]
>>> mx = 2
>>> qfx, dfx = fm[mx]
>>> fsv_single = fsv[mx]
>>> fs_single = fs[mx]
>>> # check featweights
>>> data_featweights = ibs.get_annot_fgweights([aid])[0]
>>> data_featweights[dfx]
>>> fnum = pt.next_fnum()
>>> bad_aid = cm.get_top_aids()[0]
>>> #match_interaction_good = interact_matches.MatchInteraction(ibs, cm, aid, annot_mode=1)
>>> #match_interaction_bad = interact_matches.MatchInteraction(ibs, cm, bad_aid)
>>> match_interaction_good = cm.ishow_matches(ibs, aid, annot_mode=1, fnum=1)
>>> match_interaction_bad = cm.ishow_matches(ibs, bad_aid, annot_mode=1, fnum=2)
>>> match_interaction = match_interaction_good
>>> self = match_interaction
>>> self.select_ith_match(mx)
>>> #impossible_to_match = len(correct_indices) > 0
"""
y = """
>>> from os.path import exists
>>> import vtool as vt
>>> import vtool.patch as vtpatch
>>> import vtool.image as vtimage # NOQA
>>> chip_list = ibs.get_annot_chips([aid])
>>> kpts_list = ibs.get_annot_kpts([aid])
>>> probchip_fpath_list = ibs.get_probchip_fpath(aid)
>>> probchip_list = [vt.imread(fpath, grayscale=True) if exists(fpath) else None for fpath in probchip_fpath_list]
>>> kpts = kpts_list[0]
>>> probchip = probchip_list[0]
>>> kp = kpts[dfx]
>>> patch = vt.get_warped_patch(probchip, kp)[0].astype(np.float32) / 255.0
>>> fnum2 = pt.next_fnum()
>>> pt.figure(fnum2, pnum=(1, 2, 1), doclf=True, docla=True)
>>> pt.imshow(probchip)
>>> pt.draw_kpts2([kp])
>>> pt.figure(fnum2, pnum=(1, 2, 2))
>>> pt.imshow(patch * 255)
>>> pt.update()
>>> vt.gaussian_average_patch(patch)
>>> cm.ishow_top(ibs, annot_mode=1)
"""
y
ut.set_clipboard(IPYTHON_COMMANDS)
#ut.spawn_delayed_ipython_paste()
ut.embed(remove_pyqt_hook=False)
IPYTHON_COMMANDS
testcases[case].append(testtup)
for qaid in six.iterkeys(qaid2_qres_vsmany):
qres_vsmany = qaid2_qres_vsmany[qaid]
qres_vsone = qaid2_qres_vsone[qaid]
nscoretup_vsone = qres_vsone.get_nscoretup()
nscoretup_vsmany = qres_vsmany.get_nscoretup()
metatup = incinfo['metatup']
ibs_gt, aid1_to_aid2 = metatup
aid2_to_aid1 = ut.invert_dict(aid1_to_aid2)
top_aids_vsone = ut.get_list_column(nscoretup_vsone.sorted_aids, 0)
top_aids_vsmany = ut.get_list_column(nscoretup_vsmany.sorted_aids, 0)
# tranform to groundtruth database coordinates
all_daids_t = ut.dict_take_list(aid2_to_aid1, daids)
top_aids_vsone_t = ut.dict_take_list(aid2_to_aid1, top_aids_vsone)
top_aids_vsmany_t = ut.dict_take_list(aid2_to_aid1, top_aids_vsmany)
qaid_t = aid2_to_aid1[qaid]
aids_tup = (all_daids_t, top_aids_vsone_t, top_aids_vsmany_t, (qaid_t,),)
nids_tup = ibs_gt.unflat_map(ibs_gt.get_annot_nids, aids_tup)
(all_nids_t, top_nids_vsone_t, top_nids_vsmany_t, (qnid_t,),) = nids_tup
vsmany_rank = ut.listfind(top_nids_vsmany_t, qnid_t)
vsone_rank = ut.listfind(top_nids_vsone_t, qnid_t)
impossible_to_match = ut.listfind(all_nids_t, qnid_t) is None
# Sort the test case into a category
testtup = TestTup(qaid_t, qaid, vsmany_rank, vsone_rank)
if vsmany_rank is None and vsone_rank is None and impossible_to_match:
append_case(SINGLETON, testtup)
elif vsmany_rank is not None and vsone_rank is None:
if vsmany_rank < 5:
append_case(VSMANY_DOMINATES, testtup)
else:
append_case(VSMANY_OUTPERFORMED, testtup)
elif vsmany_rank is None:
append_case(BOTH_FAIL, testtup)
elif vsone_rank > vsmany_rank:
append_case(VSMANY_WINS, testtup)
elif vsone_rank < vsmany_rank:
append_case(VSONE_WINS, testtup)
elif vsone_rank == vsmany_rank:
append_case(WASH, testtup)
else:
raise AssertionError('unenumerated case')
count_dict = ut.count_dict_vals(testcases)
print('+--')
#print(ut.dict_str(testcases))
print('---')
print(ut.dict_str(count_dict))
print('L__')
