def testdata_showchip():
import ibeis
ibs = ibeis.opendb(defaultdb='PZ_MTEST')
aid_list = ut.get_argval(('--aids', '--aid'), type_=list, default=None)
if aid_list is None:
aid_list = ibs.get_valid_aids()[0:4]
weight_label = ut.get_argval('--weight_label',
type_=str,
default='fg_weights')
annote = not ut.get_argflag('--no-annote')
kwargs = dict(ori=ut.get_argflag('--ori'),
weight_label=weight_label,
annote=annote)
kwargs['notitle'] = ut.get_argflag('--notitle')
kwargs['pts'] = ut.get_argflag('--drawpts')
kwargs['ell'] = ut.get_argflag('--drawell')
kwargs['ell_alpha'] = ut.get_argval('--ellalpha', default=.4)
kwargs['ell_linewidth'] = ut.get_argval('--ell_linewidth', default=2)
ut.print_dict(kwargs)
default_config = dict(
ibeis.algo.Config.FeatureWeightConfig().parse_items())
cfgdict = ut.argparse_dict(default_config)
print('[viz_chip.testdata] cfgdict = %r' % (cfgdict, ))
config2_ = ibs.new_query_params(cfgdict=cfgdict)
print('query_cfgstr = ' + config2_.query_cfgstr)
print('feat_cfgstr = ' + config2_.feat_cfgstr)
print('[viz_chip.testdata] aid_list = %r' % (aid_list, ))
return ibs, aid_list, kwargs, config2_
def on_click_inside(self, event, ax):
from plottool import plot_helpers as ph
ibs = self.ibs
viztype = ph.get_plotdat(ax, 'viztype', '')
is_match_type = viztype in ['matches', 'multi_match']
key = '' if event.key is None else event.key
print('key=%r ' % key)
ctrl_down = key.find('control') == 0
# Click in match axes
if event.button == 3:
return super(MatchInteraction, self).on_click_inside(event, ax)
if is_match_type and ctrl_down:
# Ctrl-Click
print('.. control click')
return self.sv_view()
elif viztype in ['warped', 'unwarped']:
print('clicked at patch')
ut.print_dict(ph.get_plotdat_dict(ax))
hs_aid = {
'aid1': self.qaid,
'aid2': self.daid,
}[vh.get_ibsdat(ax, 'aid', None)]
hs_fx = vh.get_ibsdat(ax, 'fx', None)
print('hs_fx = %r' % (hs_fx,))
print('hs_aid = %r' % (hs_aid,))
if hs_aid is not None and viztype == 'unwarped':
ishow_chip(ibs, hs_aid, fx=hs_fx, fnum=pt.next_fnum())
elif hs_aid is not None and viztype == 'warped':
viz.show_keypoint_gradient_orientations(ibs, hs_aid, hs_fx,
fnum=pt.next_fnum())
else:
return super(MatchInteraction, self).on_click_inside(event, ax)
self.draw()
def __init__(bing,
default=True,
verbose=VERBOSE_BING,
quiet=QUIET_BING,
**kwargs):
'''
Create the C object for the PyBING detector.
Args:
verbose (bool, optional): verbose flag; defaults to --verbbing flag
Kwargs:
base (int)
W (int)
NNS (int)
Returns:
detector (object): the BING Detector object
'''
bing.verbose = verbose
bing.quiet = quiet
# Default values
params = odict([
('base', 2.0),
('W', 8),
('NNS', 2),
('verbose', verbose),
('quiet', quiet),
])
params.update(kwargs)
params_list = list(params.values())
if bing.verbose and not bing.quiet:
""" debug with dmesg | tail -n 200 """
print('[pybing.py] Start Create New BING Object')
ut.print_dict(params)
print('[pybing.py] params_list = %r' % (params_list, ))
print('[pybing.py] type of params = %r' %
(list(map(type, params_list)), ))
pass
bing.detector_c_obj = BING_CLIB.init(*params_list)
if bing.verbose and not bing.quiet:
print('[pybing.py] Finished Create New BING Object')
if default:
model_path = ut.grab_zipped_url(VOC2007_MODEL_URL,
appname='pybing')
model_path = join(model_path, 'model')
print('Loading models: %r' % (model_path, ))
bing.model(model_path)
def __init__(bing, default=True, verbose=VERBOSE_BING, quiet=QUIET_BING, **kwargs):
'''
Create the C object for the PyBING detector.
Args:
verbose (bool, optional): verbose flag; defaults to --verbbing flag
Kwargs:
base (int)
W (int)
NNS (int)
Returns:
detector (object): the BING Detector object
'''
bing.verbose = verbose
bing.quiet = quiet
# Default values
params = odict([
('base', 2.0),
('W', 8),
('NNS', 2),
('verbose', verbose),
('quiet', quiet),
])
params.update(kwargs)
params_list = list(params.values())
if bing.verbose and not bing.quiet:
""" debug with dmesg | tail -n 200 """
print('[pybing.py] Start Create New BING Object')
ut.print_dict(params)
print('[pybing.py] params_list = %r' % (params_list,))
print('[pybing.py] type of params = %r' % (list(map(type, params_list)),))
pass
bing.detector_c_obj = BING_CLIB.init(*params_list)
if bing.verbose and not bing.quiet:
print('[pybing.py] Finished Create New BING Object')
if default:
model_path = ut.grab_zipped_url(VOC2007_MODEL_URL, appname='pybing')
model_path = join(model_path, 'model')
print('Loading models: %r' % (model_path, ))
bing.model(model_path)
def __init__(self, **kwargs):
#self.num_engines = 3
self.num_engines = NUM_ENGINES
self.engine_queue_proc = None
self.collect_queue_proc = None
self.engine_procs = None
self.collect_proc = None
# --
only_engine = ut.get_argflag('--only-engine')
self.spawn_collector = not only_engine
self.spawn_engine = not ut.get_argflag('--no-engine')
self.fg_engine = ut.get_argflag('--fg-engine')
self.spawn_queue = not only_engine
# Find ports
self.port_dict = None
self._initialize_job_ports(**kwargs)
print('JobBackend ports:')
ut.print_dict(self.port_dict)
def __debug_win_msvcr():
import utool as ut
fname = 'msvcr*.dll'
key_list = ['PATH']
found = ut.search_env_paths(fname, key_list)
fpaths = ut.unique(ut.flatten(found.values()))
fpaths = ut.lmap(ut.ensure_unixslash, fpaths)
from os.path import basename
dllnames = [basename(x) for x in fpaths]
grouped = dict(ut.group_items(fpaths, dllnames))
print(ut.dict_str(grouped, nl=4))
keytoid = {}
for key, vals in grouped.items():
infos = ut.lmap(ut.get_file_nBytes, vals)
#infos = ut.lmap(ut.get_file_uuid, vals)
#uuids = [ut.get_file_uuid(val) for val in vals]
keytoid[key] = list(zip(infos, vals))
ut.print_dict(keytoid, nl=2)
def __debug_win_msvcr():
import utool as ut
fname = 'msvcr*.dll'
key_list = ['PATH']
found = ut.search_env_paths(fname, key_list)
fpaths = ut.unique(ut.flatten(found.values()))
fpaths = ut.lmap(ut.ensure_unixslash, fpaths)
from os.path import basename
dllnames = [basename(x) for x in fpaths]
grouped = dict(ut.group_items(fpaths, dllnames))
print(ut.repr4(grouped, nl=4))
keytoid = {
}
for key, vals in grouped.items():
infos = ut.lmap(ut.get_file_nBytes, vals)
#infos = ut.lmap(ut.get_file_uuid, vals)
#uuids = [ut.get_file_uuid(val) for val in vals]
keytoid[key] = list(zip(infos, vals))
ut.print_dict(keytoid, nl=2)
def testdata_showchip():
import ibeis
ibs = ibeis.opendb(defaultdb='PZ_MTEST')
aid_list = ut.get_argval(('--aids', '--aid'), type_=list, default=None)
if aid_list is None:
aid_list = ibs.get_valid_aids()[0:4]
weight_label = ut.get_argval('--weight_label', type_=str, default='fg_weights')
annote = not ut.get_argflag('--no-annote')
kwargs = dict(ori=ut.get_argflag('--ori'), weight_label=weight_label, annote=annote)
kwargs['notitle'] = ut.get_argflag('--notitle')
kwargs['pts'] = ut.get_argflag('--drawpts')
kwargs['ell'] = ut.get_argflag('--drawell')
kwargs['ell_alpha'] = ut.get_argval('--ellalpha', default=.4)
kwargs['ell_linewidth'] = ut.get_argval('--ell_linewidth', default=2)
ut.print_dict(kwargs)
default_config = dict(ibeis.algo.Config.FeatureWeightConfig().parse_items())
cfgdict = ut.argparse_dict(default_config)
print('[viz_chip.testdata] cfgdict = %r' % (cfgdict,))
config2_ = ibs.new_query_params(cfgdict=cfgdict)
print('query_cfgstr = ' + config2_.query_cfgstr)
print('feat_cfgstr = ' + config2_.feat_cfgstr)
print('[viz_chip.testdata] aid_list = %r' % (aid_list,))
return ibs, aid_list, kwargs, config2_
def on_click(self, event):
aid = self.daid
qaid = self.qaid
ibs = self.ibs
xywh2_ptr = self.xywh2_ptr
print('[inter] clicked matches')
if event is None:
return
button = event.button
is_right_click = button == 3
# Out of axes click
(x, y, ax) = (event.xdata, event.ydata, event.inaxes)
if None in [x, y, ax]:
in_axis = False
if not is_right_click:
print('... out of axis')
self.chipmatch_view()
viz.draw()
return
else:
in_axis = True
if in_axis:
viztype = vh.get_ibsdat(ax, 'viztype', '')
is_match_type = viztype in ['matches', 'multi_match']
print('[ir] viztype=%r ' % viztype)
else:
is_match_type = False
viztype = ''
if is_right_click:
from ibeis.gui import inspect_gui
options = []
if is_match_type:
options += inspect_gui.get_aidpair_context_menu_options(
self.ibs,
self.qaid,
self.daid,
self.cm,
qreq_=self.qreq_,
#update_callback=self.show_page,
#backend_callback=None, aid_list=aid_list)
)
options += [
('Toggle same_fig', self.toggle_samefig),
('Toggle vert', self.toggle_vert),
('query last feature', self.query_last_feature),
('show each chip', self.show_each_chip),
('show each distinctiveness chip',
self.show_each_dstncvs_chip),
('show each foreground weight chip',
self.show_each_fgweight_chip),
('show each probchip', self.show_each_probchip),
('show coverage', self.show_coverage),
#('show each probchip', self.query_last_feature),
]
#options.append(('name_interaction', self.name_interaction))
if self.H1 is not None:
options.append(('Toggle homog', self.toggle_homog))
if ut.is_developer():
options.append(('dev_reload', self.dev_reload))
options.append(('dev_embed', self.dev_embed))
#options.append(('cancel', lambda: print('cancel')))
self.show_popup_menu(options, event)
return
if in_axis:
key = '' if event.key is None else event.key
print('key=%r ' % key)
ctrl_down = key.find('control') == 0
# Click in match axes
if is_match_type and ctrl_down:
# Ctrl-Click
print('.. control click')
return self.sv_view()
elif is_match_type:
if len(self.fm) == 0:
print('[inter] no feature matches to click')
else:
# Normal Click
# Select nearest feature match to the click
kpts1 = ibs.get_annot_kpts([qaid],
config2_=self.query_config2_)[0]
kpts2 = ibs.get_annot_kpts([aid],
config2_=self.data_config2_)[0]
kpts1_m = kpts1[self.fm.T[0]]
kpts2_m = kpts2[self.fm.T[1]]
x2, y2, w2, h2 = xywh2_ptr[0]
_mx1, _dist1 = ut.nearest_point(x, y, kpts1_m)
_mx2, _dist2 = ut.nearest_point(x - x2, y - y2, kpts2_m)
mx = _mx1 if _dist1 < _dist2 else _mx2
(fx1, fx2) = self.fm[mx]
print('... clicked mx=%r' % mx)
print('... fx1, fx2 = %r, %r' % (
fx1,
fx2,
))
self.select_ith_match(mx)
elif viztype in ['warped', 'unwarped']:
print('clicked at patch')
ut.print_dict(ph.get_plotdat_dict(ax))
hs_aid = vh.get_ibsdat(ax, 'aid', None)
hs_fx = vh.get_ibsdat(ax, 'fx', None)
#hs_aid = ax.__dict__.get('_hs_aid', None)
#hs_fx = ax.__dict__.get('_hs_fx', None)
print('hs_fx = %r' % (hs_fx, ))
print('hs_aid = %r' % (hs_aid, ))
if hs_aid is not None and viztype == 'unwarped':
ishow_chip(ibs, hs_aid, fx=hs_fx, fnum=df2.next_fnum())
elif hs_aid is not None and viztype == 'warped':
viz.show_keypoint_gradient_orientations(
ibs, hs_aid, hs_fx, fnum=df2.next_fnum())
elif viztype.startswith('colorbar'):
# Hack to get a specific scoring feature
sortx = self.fs.argsort()
idx = np.clip(int(np.round(y * len(sortx))), 0, len(sortx) - 1)
mx = sortx[idx]
(fx1, fx2) = self.fm[mx]
(fx1, fx2) = self.fm[mx]
print('... selected score at rank idx=%r' % (idx, ))
print('... selected score with fs=%r' % (self.fs[mx], ))
print('... resolved to mx=%r' % mx)
print('... fx1, fx2 = %r, %r' % (
fx1,
fx2,
))
self.select_ith_match(mx)
else:
print('...Unknown viztype: %r' % viztype)
viz.draw()
def __init__(jobiface, id_, port_dict):
jobiface.id_ = id_
jobiface.verbose = 2 if VERBOSE_JOBS else 1
jobiface.port_dict = port_dict
print('JobInterface ports:')
ut.print_dict(jobiface.port_dict)
def compute_occurrence_groups(ibs, gid_list, config={}, use_gps=False, verbose=None):
r"""
Args:
ibs (IBEISController): wbia controller object
gid_list (list):
Returns:
tuple: (None, None)
CommandLine:
python -m wbia compute_occurrence_groups
Example:
>>> # DISABLE_DOCTEST
>>> from wbia.algo.preproc.preproc_occurrence import * # NOQA
>>> import wbia
>>> ibs = wbia.opendb(defaultdb='testdb1')
>>> verbose = True
>>> images = ibs.images()
>>> gid_list = images.gids
>>> config = {} # wbia.algo.Config.OccurrenceConfig().asdict()
>>> tup = wbia_compute_occurrences(ibs, gid_list)
>>> (flat_imgsetids, flat_gids)
>>> aids_list = list(ut.group_items(aid_list_, flat_imgsetids).values())
>>> metric = list(map(len, aids_list))
>>> sortx = ut.list_argsort(metric)[::-1]
>>> index = sortx[1]
>>> aids = aids_list[index]
>>> gids = list(set(ibs.get_annot_gids(aids)))
"""
if verbose is None:
verbose = ut.NOT_QUIET
# Config info
gid_list = np.unique(gid_list)
if verbose:
logger.info('[occur] Computing occurrences on %r images.' % (len(gid_list)))
logger.info('[occur] config = ' + ut.repr3(config))
use_gps = config['use_gps']
datas = prepare_X_data(ibs, gid_list, use_gps=use_gps)
from wbia.algo.preproc import occurrence_blackbox
cluster_algo = config.get('cluster_algo', 'agglomerative')
km_per_sec = config.get('km_per_sec', occurrence_blackbox.KM_PER_SEC)
thresh_sec = config.get('seconds_thresh', 30 * 60.0)
min_imgs_per_occurence = config.get('min_imgs_per_occurence', 1)
# 30 minutes = 3.6 kilometers
# 5 minutes = 0.6 kilometers
assert cluster_algo == 'agglomerative', 'only agglomerative is supported'
# Group datas with different values separately
all_gids = []
all_labels = []
for key in datas.keys():
val = datas[key]
gids, latlons, posixtimes = val
labels = occurrence_blackbox.cluster_timespace_sec(
latlons, posixtimes, thresh_sec, km_per_sec=km_per_sec
)
if labels is None:
labels = np.zeros(len(gids), dtype=np.int)
all_gids.append(gids)
all_labels.append(labels)
# Combine labels across different groups
pads = [vt.safe_max(ys, fill=0) + 1 for ys in all_labels]
offsets = np.array([0] + pads[:-1]).cumsum()
all_labels_ = [ys + offset for ys, offset in zip(all_labels, offsets)]
label_arr = np.array(ut.flatten(all_labels_))
gid_arr = np.array(ut.flatten(all_gids))
# Group images by unique label
labels, label_gids = group_images_by_label(label_arr, gid_arr)
# Remove occurrences less than the threshold
occur_labels = labels
occur_gids = label_gids
occur_unixtimes = compute_occurrence_unixtime(ibs, occur_gids)
occur_labels, occur_gids = filter_and_relabel(
labels, label_gids, min_imgs_per_occurence, occur_unixtimes
)
if verbose:
logger.info('[occur] Found %d clusters.' % len(occur_labels))
if len(label_gids) > 0 and verbose:
logger.info('[occur] Cluster image size stats:')
ut.print_dict(
ut.get_stats(list(map(len, occur_gids)), use_median=True, use_sum=True),
'occur image stats',
)
return occur_labels, occur_gids
def on_click(self, event):
aid = self.daid
qaid = self.qaid
ibs = self.ibs
xywh2_ptr = self.xywh2_ptr
print('[inter] clicked matches')
if event is None:
return
button = event.button
is_right_click = button == 3
# Out of axes click
(x, y, ax) = (event.xdata, event.ydata, event.inaxes)
if None in [x, y, ax]:
in_axis = False
if not is_right_click:
print('... out of axis')
self.chipmatch_view()
viz.draw()
return
else:
in_axis = True
if in_axis:
viztype = vh.get_ibsdat(ax, 'viztype', '')
is_match_type = viztype in ['matches', 'multi_match']
print('[ir] viztype=%r ' % viztype)
else:
is_match_type = False
viztype = ''
if is_right_click:
from ibeis.gui import inspect_gui
options = []
if is_match_type:
options += inspect_gui.get_aidpair_context_menu_options(
self.ibs, self.qaid, self.daid, self.cm,
qreq_=self.qreq_,
#update_callback=self.show_page,
#backend_callback=None, aid_list=aid_list)
)
options += [
('Toggle same_fig', self.toggle_samefig),
('Toggle vert', self.toggle_vert),
('query last feature', self.query_last_feature),
('show each chip', self.show_each_chip),
('show each distinctiveness chip', self.show_each_dstncvs_chip),
('show each foreground weight chip', self.show_each_fgweight_chip),
('show each probchip', self.show_each_probchip),
('show coverage', self.show_coverage),
#('show each probchip', self.query_last_feature),
]
#options.append(('name_interaction', self.name_interaction))
if self.H1 is not None:
options.append(('Toggle homog', self.toggle_homog))
if ut.is_developer():
options.append(('dev_reload', self.dev_reload))
options.append(('dev_embed', self.dev_embed))
#options.append(('cancel', lambda: print('cancel')))
self.show_popup_menu(options, event)
return
if in_axis:
key = '' if event.key is None else event.key
print('key=%r ' % key)
ctrl_down = key.find('control') == 0
# Click in match axes
if is_match_type and ctrl_down:
# Ctrl-Click
print('.. control click')
return self.sv_view()
elif is_match_type:
if len(self.fm) == 0:
print('[inter] no feature matches to click')
else:
# Normal Click
# Select nearest feature match to the click
kpts1 = ibs.get_annot_kpts([qaid], config2_=self.query_config2_)[0]
kpts2 = ibs.get_annot_kpts([aid], config2_=self.data_config2_)[0]
kpts1_m = kpts1[self.fm.T[0]]
kpts2_m = kpts2[self.fm.T[1]]
x2, y2, w2, h2 = xywh2_ptr[0]
_mx1, _dist1 = ut.nearest_point(x, y, kpts1_m)
_mx2, _dist2 = ut.nearest_point(x - x2, y - y2, kpts2_m)
mx = _mx1 if _dist1 < _dist2 else _mx2
(fx1, fx2) = self.fm[mx]
print('... clicked mx=%r' % mx)
print('... fx1, fx2 = %r, %r' % (fx1, fx2,))
self.select_ith_match(mx)
elif viztype in ['warped', 'unwarped']:
print('clicked at patch')
ut.print_dict(ph.get_plotdat_dict(ax))
hs_aid = vh.get_ibsdat(ax, 'aid', None)
hs_fx = vh.get_ibsdat(ax, 'fx', None)
#hs_aid = ax.__dict__.get('_hs_aid', None)
#hs_fx = ax.__dict__.get('_hs_fx', None)
print('hs_fx = %r' % (hs_fx,))
print('hs_aid = %r' % (hs_aid,))
if hs_aid is not None and viztype == 'unwarped':
ishow_chip(ibs, hs_aid, fx=hs_fx, fnum=df2.next_fnum())
elif hs_aid is not None and viztype == 'warped':
viz.show_keypoint_gradient_orientations(ibs, hs_aid, hs_fx,
fnum=df2.next_fnum())
elif viztype.startswith('colorbar'):
# Hack to get a specific scoring feature
sortx = self.fs.argsort()
idx = np.clip(int(np.round(y * len(sortx))), 0, len(sortx) - 1)
mx = sortx[idx]
(fx1, fx2) = self.fm[mx]
(fx1, fx2) = self.fm[mx]
print('... selected score at rank idx=%r' % (idx,))
print('... selected score with fs=%r' % (self.fs[mx],))
print('... resolved to mx=%r' % mx)
print('... fx1, fx2 = %r, %r' % (fx1, fx2,))
self.select_ith_match(mx)
else:
print('...Unknown viztype: %r' % viztype)
viz.draw()
def compute_occurrence_groups(ibs, gid_list, cluster_algo, cfgdict={}, use_gps=False, verbose=None):
r"""
Args:
ibs (IBEISController): ibeis controller object
gid_list (list):
Returns:
tuple: (None, None)
CommandLine:
python -m ibeis --tf compute_occurrence_groups
python -m ibeis --tf compute_occurrence_groups --show --zoom=.3
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.algo.preproc.preproc_occurrence import * # NOQA
>>> import ibeis
>>> import vtool as vt
>>> #ibs = ibeis.opendb(defaultdb='testdb1')
>>> ibs = ibeis.opendb(defaultdb='PZ_Master1')
>>> gid_list = ibs.get_valid_gids(require_unixtime=True, require_gps=True)
>>> use_gps = True
>>> cluster_algo = 'meanshift'
>>> cfgdict = dict(quantile=.005, min_imgs_per_occurence=2)
>>> (occur_labels, occur_gids) = compute_occurrence_groups(ibs, gid_list, cluster_algo, cfgdict, use_gps=use_gps)
>>> aidsgroups_list = ibs.unflat_map(ibs.get_image_aids, occur_gids)
>>> aids_list = list(map(ut.flatten, aidsgroups_list))
>>> nids_list = list(map(np.array, ibs.unflat_map(ibs.get_annot_name_rowids, aids_list)))
>>> metric = [len(np.unique(nids[nids > -1])) for nids in nids_list]
>>> metric = [vt.safe_max(np.array(ut.dict_hist(nids).values())) for nids in nids_list]
>>> #metric = list(map(len, aids_list))
>>> sortx = ut.list_argsort(metric)[::-1]
>>> index = sortx[20]
>>> #gids = occur_gids[index]
>>> aids = aids_list[index]
>>> aids = ibs.filter_annots_general(aids, min_qual='ok', is_known=True)
>>> gids = list(set(ibs.get_annot_gids(aids)))
>>> print('len(aids) = %r' % (len(aids),))
>>> img_list = ibs.get_images(gids)
>>> ut.quit_if_noshow()
>>> from ibeis.viz import viz_graph
>>> import plottool as pt
>>> #pt.imshow(bigimg)
>>> #aids = ibs.group_annots_by_name(aids)[0][0]
>>> self = viz_graph.make_name_graph_interaction(ibs, aids=aids,
>>> with_all=False,
>>> prog='neato')
>>> ut.show_if_requested()
ibs.unflat_map(ibs.get_annot_case_tags, aids_list)
ibs.filter_aidpairs_by_tags(has_any='photobomb')
photobomb_aids = ibs.filter_aidpairs_by_tags(has_any='photobomb')
aids = photobomb_aids[0:10].flatten()
_gt_aids = ibs.get_annot_groundtruth(aids)
gt_aids = ut.get_list_column_slice(_gt_aids, slice(0, 3))
aid_set = np.unique(np.append(aids.flatten(), ut.flatten(gt_aids)))
aid_set = ibs.filter_annots_general(aid_set, minqual='ok')
# This is the set of annotations used for testing intraoccurrence photobombs
#print(ut.repr3(ibeis.other.dbinfo.get_dbinfo(ibs, aid_list=aid_set), strvals=True, nl=1))
print(ut.repr3(ibs.get_annot_stats_dict(aid_set, forceall=True), strvals=True, nl=1))
"""
if verbose is None:
verbose = ut.NOT_QUIET
# Config info
gid_list = np.unique(gid_list)
if verbose:
print("[occur] Computing %r occurrences on %r images." % (cluster_algo, len(gid_list)))
if len(gid_list) == 0:
print("[occur] WARNING: len(gid_list) == 0. " "No images to compute occurrences with")
occur_labels, occur_gids = [], []
else:
if len(gid_list) == 1:
print("[occur] WARNING: custering 1 image into its own occurrence")
gid_arr = np.array(gid_list)
label_arr = np.zeros(gid_arr.shape)
else:
X_data, gid_arr = prepare_X_data(ibs, gid_list, use_gps=use_gps)
# Agglomerative clustering of unixtimes
if cluster_algo == "agglomerative":
seconds_thresh = cfgdict.get("seconds_thresh", 60.0)
label_arr = agglomerative_cluster_occurrences(X_data, seconds_thresh)
elif cluster_algo == "meanshift":
quantile = cfgdict.get("quantile", 0.01)
label_arr = meanshift_cluster_occurrences(X_data, quantile)
else:
raise AssertionError("[occurrence] Uknown clustering algorithm: %r" % cluster_algo)
# Group images by unique label
labels, label_gids = group_images_by_label(label_arr, gid_arr)
# Remove occurrences less than the threshold
occur_labels = labels
occur_gids = label_gids
occur_unixtimes = compute_occurrence_unixtime(ibs, occur_gids)
min_imgs_per_occurence = cfgdict.get("min_imgs_per_occurence", 1)
occur_labels, occur_gids = filter_and_relabel(labels, label_gids, min_imgs_per_occurence, occur_unixtimes)
if verbose:
print("[occur] Found %d clusters." % len(occur_labels))
if len(label_gids) > 0 and verbose:
print("[occur] Cluster image size stats:")
ut.print_dict(ut.get_stats(list(map(len, occur_gids)), use_median=True, use_sum=True), "occur image stats")
return occur_labels, occur_gids
