def test_pref(): guitool.ensure_qtapp() import utool root = utool.Pref(name='mypref') root.pref1 = 5 root.pref2 = 'string' root.pref3 = 'True' root.pref4 = True root.pref5 = utool.Pref(name='child') root.pref5.pref6 = 3.5 root.createQWidget() return root
def _init_gui(activate=True): import guitool if NOT_QUIET: print('[main] _init_gui()') guitool.ensure_qtapp() #USE_OLD_BACKEND = '--old-backend' in sys.argv #if USE_OLD_BACKEND: from ibeis.gui import guiback back = guiback.MainWindowBackend() #else: # from ibeis.gui import newgui # back = newgui.IBEISGuiWidget() if activate: guitool.activate_qwindow(back.mainwin) return back
def start_qt_interface(infr, loop=True): import guitool as gt from ibeis.viz.viz_graph2 import AnnotGraphWidget from plottool import abstract_interaction import plottool as pt pt.qtensure() gt.ensure_qtapp() # win = AnnotGraphWidget(infr=infr, use_image=False, init_mode='review') win = AnnotGraphWidget(infr=infr, use_image=False, init_mode=None) abstract_interaction.register_interaction(win) if loop: gt.qtapp_loop(qwin=win, freq=10) else: win.show() return win
def guiselect_workdir(): """ Prompts the user to specify a work directory """ import guitool guitool.ensure_qtapp() # Gui selection work_dir = guitool.select_directory('Select a work directory') # Make sure selection is ok if not exists(work_dir): try_again = guitool.user_option( paremt=None, msg='Directory %r does not exist.' % work_dir, title='get work dir failed', options=['Try Again'], use_cache=False) if try_again == 'Try Again': return guiselect_workdir() return work_dir
def guiselect_workdir(): """ Prompts the user to specify a work directory """ import guitool guitool.ensure_qtapp() # Gui selection work_dir = guitool.select_directory('Select a work directory') # Make sure selection is ok if not exists(work_dir): try_again = guitool.user_option(paremt=None, msg='Directory %r does not exist.' % work_dir, title='get work dir failed', options=['Try Again'], use_cache=False) if try_again == 'Try Again': return guiselect_workdir() return work_dir
def fix_splits_interaction(ibs): """ python -m ibeis fix_splits_interaction --show Example: >>> # DISABLE_DOCTEST GGR >>> from ibeis.other.dbinfo import * # NOQA >>> import ibeis >>> dbdir = '/media/danger/GGR/GGR-IBEIS' >>> dbdir = dbdir if ut.checkpath(dbdir) else ut.truepath('~/lev/media/danger/GGR/GGR-IBEIS') >>> ibs = ibeis.opendb(dbdir=dbdir, allow_newdir=False) >>> import guitool as gt >>> gt.ensure_qtapp() >>> win = fix_splits_interaction(ibs) >>> ut.quit_if_noshow() >>> import plottool as pt >>> gt.qtapp_loop(qwin=win) """ split_props = {'splitcase', 'photobomb'} all_annot_groups = ibs._annot_groups(ibs.group_annots_by_name(ibs.get_valid_aids())[0]) all_has_split = [len(split_props.intersection(ut.flatten(tags))) > 0 for tags in all_annot_groups.match_tags] tosplit_annots = ut.compress(all_annot_groups.annots_list, all_has_split) tosplit_annots = ut.take(tosplit_annots, ut.argsort(ut.lmap(len, tosplit_annots)))[::-1] if ut.get_argflag('--reverse'): tosplit_annots = tosplit_annots[::-1] print('len(tosplit_annots) = %r' % (len(tosplit_annots),)) aids_list = [a.aids for a in tosplit_annots] from ibeis.algo.graph import graph_iden from ibeis.viz import viz_graph2 import guitool as gt import plottool as pt pt.qt4ensure() gt.ensure_qtapp() for aids in ut.InteractiveIter(aids_list): infr = graph_iden.AnnotInference(ibs, aids) infr.initialize_graph() win = viz_graph2.AnnotGraphWidget(infr=infr, use_image=False, init_mode='rereview') win.populate_edge_model() win.show() return win
# eid = model.eid gid = id_ print("SINGLE CLICKED ID: %r" % gid) @slot_(QtCore.QModelIndex) def on_doubleclick(ibswgt, qtindex): printDBG('on_doubleclick') model = qtindex.model() id_ = model._get_row_id(qtindex) if model.name == NAMES_TREE: # eid = model.eid gid = id_ #ibswgt.annotation_interact = interact_annotations2.ANNOTATION_Interaction2(ibswgt.ibs, gid) print("DOUBLECLICKED ID: %r" % gid) if __name__ == '__main__': import ibeis import sys ibeis._preload(mpl=False, par=False) guitool.ensure_qtapp() dbdir = ibeis.sysres.get_args_dbdir(defaultdb='cache') ibs = IBEISControl.IBEISController(dbdir=dbdir) ibswgt = IBEISGuiWidget(ibs=ibs) ibswgt.resize(900, 600) if '--cmd' in sys.argv: guitool.qtapp_loop(qwin=ibswgt, ipy=True) exec(utool.ipython_execstr()) else: guitool.qtapp_loop(qwin=ibswgt)
def edit_config(self, event): import guitool guitool.ensure_qtapp() from guitool import PrefWidget2 self.widget = PrefWidget2.EditConfigWidget(config=self.config) self.widget.show()
def test_inc_query(ibs_gt, num_initial=0): """ entry point for interactive query tests test_interactive_incremental_queries Args: ibs (list) : IBEISController object qaid_list (list) : list of annotation-ids to query CommandLine: python dev.py -t inc --db PZ_MTEST --qaid 1:30:3 --cmd python dev.py --db PZ_MTEST --allgt --cmd python dev.py --db PZ_MTEST --allgt -t inc python dev.py --db PZ_MTEST --allgt -t inc CommandLine: python -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:0 --interact-after 444440 --noqcache python -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:1 --interact-after 444440 --noqcache python -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:0 python -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:1 python -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:2 python -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:3 utprof.py -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:3 --ninit 5000 utprof.py -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:0 # Writes out test script python -c "import utool as ut; ut.write_modscript_alias('Tinc.sh', 'ibeis.algo.hots.qt_inc_automatch')" sh Tinc.sh --test-test_inc_query:0 sh Tinc.sh --test-test_inc_query:1 sh Tinc.sh --test-test_inc_query:2 sh Tinc.sh --test-test_inc_query:3 utprof.py -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:3 --num-init 5000 sh Tinc.sh --test-test_inc_query:0 --ninit 10 sh Tinc.sh --test-test_inc_query:0 --ninit 10 --verbose-debug --verbose-helpful python -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:0 --ia 10 # Runs into a merge case python -m ibeis.algo.hots.qt_inc_automatch --test-test_inc_query:0 --ia 30 Example0: >>> # DISABLE_DOCTEST >>> from ibeis.algo.hots.automated_matcher import * # NOQA >>> ibs_gt = ibeis.opendb('testdb1') >>> test_inc_query(ibs_gt) Example1: >>> # DISABLE_DOCTEST >>> from ibeis.algo.hots.automated_matcher import * # NOQA >>> ibs_gt = ibeis.opendb('PZ_MTEST') >>> test_inc_query(ibs_gt) Example2: >>> # DISABLE_DOCTEST >>> from ibeis.algo.hots.automated_matcher import * # NOQA >>> ibs_gt = ibeis.opendb('GZ_ALL') >>> test_inc_query(ibs_gt) Example3: >>> # DISABLE_DOCTEST >>> from ibeis.algo.hots.automated_matcher import * # NOQA >>> ibs_gt = ibeis.opendb('PZ_Master0') >>> test_inc_query(ibs_gt) """ from ibeis import main_module main_module._preload() guitool.ensure_qtapp() num_initial self = IncQueryHarness() num_initial = ut.get_argval(('--num-initial', '--num-init', '--ninit'), int, 0) interactive_after = ut.get_argval(('--interactive-after', '--ia'), type_=int, default=None) # Add information to an empty database from a groundtruth database ibs, aid_list1, aid1_to_aid2 = ah.setup_incremental_test(ibs_gt) if True or interactive_after is not None: back = main_module._init_gui() back.connect_ibeis_control(ibs) else: back = None interactive = self.test_incremental_query( ibs_gt, ibs, aid_list1, aid1_to_aid2, interactive_after=interactive_after, num_initial=num_initial, back=back) if back is None and interactive_after is None and interactive: # need to startup backend back = main_module._init_gui() back.connect_ibeis_control(ibs) if interactive or interactive_after is not None: guitool.qtapp_loop()
def split_analysis(ibs): """ CommandLine: python -m ibeis.other.dbinfo split_analysis --show python -m ibeis split_analysis --show python -m ibeis split_analysis --show --good Ignore: # mount sshfs -o idmap=user lev:/ ~/lev # unmount fusermount -u ~/lev Example: >>> # DISABLE_DOCTEST GGR >>> from ibeis.other.dbinfo import * # NOQA >>> import ibeis >>> dbdir = '/media/danger/GGR/GGR-IBEIS' >>> dbdir = dbdir if ut.checkpath(dbdir) else ut.truepath('~/lev/media/danger/GGR/GGR-IBEIS') >>> ibs = ibeis.opendb(dbdir=dbdir, allow_newdir=False) >>> import guitool as gt >>> gt.ensure_qtapp() >>> win = split_analysis(ibs) >>> ut.quit_if_noshow() >>> import plottool as pt >>> gt.qtapp_loop(qwin=win) >>> #ut.show_if_requested() """ #nid_list = ibs.get_valid_nids(filter_empty=True) import datetime day1 = datetime.date(2016, 1, 30) day2 = datetime.date(2016, 1, 31) filter_kw = { 'multiple': None, #'view': ['right'], #'minqual': 'good', 'is_known': True, 'min_pername': 1, } aids1 = ibs.filter_annots_general(filter_kw=ut.dict_union( filter_kw, { 'min_unixtime': ut.datetime_to_posixtime(ut.date_to_datetime(day1, 0.0)), 'max_unixtime': ut.datetime_to_posixtime(ut.date_to_datetime(day1, 1.0)), }) ) aids2 = ibs.filter_annots_general(filter_kw=ut.dict_union( filter_kw, { 'min_unixtime': ut.datetime_to_posixtime(ut.date_to_datetime(day2, 0.0)), 'max_unixtime': ut.datetime_to_posixtime(ut.date_to_datetime(day2, 1.0)), }) ) all_aids = aids1 + aids2 all_annots = ibs.annots(all_aids) print('%d annots on day 1' % (len(aids1)) ) print('%d annots on day 2' % (len(aids2)) ) print('%d annots overall' % (len(all_annots)) ) print('%d names overall' % (len(ut.unique(all_annots.nids))) ) nid_list, annots_list = all_annots.group(all_annots.nids) REVIEWED_EDGES = True if REVIEWED_EDGES: aids_list = [annots.aids for annots in annots_list] #aid_pairs = [annots.get_am_aidpairs() for annots in annots_list] # Slower aid_pairs = ibs.get_unflat_am_aidpairs(aids_list) # Faster else: # ALL EDGES aid_pairs = [annots.get_aidpairs() for annots in annots_list] speeds_list = ibs.unflat_map(ibs.get_annotpair_speeds, aid_pairs) import vtool as vt max_speeds = np.array([vt.safe_max(s, nans=False) for s in speeds_list]) nan_idx = np.where(np.isnan(max_speeds))[0] inf_idx = np.where(np.isinf(max_speeds))[0] bad_idx = sorted(ut.unique(ut.flatten([inf_idx, nan_idx]))) ok_idx = ut.index_complement(bad_idx, len(max_speeds)) print('#nan_idx = %r' % (len(nan_idx),)) print('#inf_idx = %r' % (len(inf_idx),)) print('#ok_idx = %r' % (len(ok_idx),)) ok_speeds = max_speeds[ok_idx] ok_nids = ut.take(nid_list, ok_idx) ok_annots = ut.take(annots_list, ok_idx) sortx = np.argsort(ok_speeds)[::-1] sorted_speeds = np.array(ut.take(ok_speeds, sortx)) sorted_annots = np.array(ut.take(ok_annots, sortx)) sorted_nids = np.array(ut.take(ok_nids, sortx)) # NOQA sorted_speeds = np.clip(sorted_speeds, 0, 100) #idx = vt.find_elbow_point(sorted_speeds) #EXCESSIVE_SPEED = sorted_speeds[idx] # http://www.infoplease.com/ipa/A0004737.html # http://www.speedofanimals.com/animals/zebra #ZEBRA_SPEED_MAX = 64 # km/h #ZEBRA_SPEED_RUN = 50 # km/h ZEBRA_SPEED_SLOW_RUN = 20 # km/h #ZEBRA_SPEED_FAST_WALK = 10 # km/h #ZEBRA_SPEED_WALK = 7 # km/h MAX_SPEED = ZEBRA_SPEED_SLOW_RUN #MAX_SPEED = ZEBRA_SPEED_WALK #MAX_SPEED = EXCESSIVE_SPEED flags = sorted_speeds > MAX_SPEED flagged_ok_annots = ut.compress(sorted_annots, flags) inf_annots = ut.take(annots_list, inf_idx) flagged_annots = inf_annots + flagged_ok_annots print('MAX_SPEED = %r km/h' % (MAX_SPEED,)) print('%d annots with infinite speed' % (len(inf_annots),)) print('%d annots with large speed' % (len(flagged_ok_annots),)) print('Marking all pairs of annots above the threshold as non-matching') from ibeis.algo.graph import graph_iden import networkx as nx progkw = dict(freq=1, bs=True, est_window=len(flagged_annots)) bad_edges_list = [] good_edges_list = [] for annots in ut.ProgIter(flagged_annots, lbl='flag speeding names', **progkw): edge_to_speeds = annots.get_speeds() bad_edges = [edge for edge, speed in edge_to_speeds.items() if speed > MAX_SPEED] good_edges = [edge for edge, speed in edge_to_speeds.items() if speed <= MAX_SPEED] bad_edges_list.append(bad_edges) good_edges_list.append(good_edges) all_bad_edges = ut.flatten(bad_edges_list) good_edges_list = ut.flatten(good_edges_list) print('num_bad_edges = %r' % (len(ut.flatten(bad_edges_list)),)) print('num_bad_edges = %r' % (len(ut.flatten(good_edges_list)),)) if 1: from ibeis.viz import viz_graph2 import guitool as gt gt.ensure_qtapp() if ut.get_argflag('--good'): print('Looking at GOOD (no speed problems) edges') aid_pairs = good_edges_list else: print('Looking at BAD (speed problems) edges') aid_pairs = all_bad_edges aids = sorted(list(set(ut.flatten(aid_pairs)))) infr = graph_iden.AnnotInference(ibs, aids, verbose=False) infr.initialize_graph() # Use random scores to randomize sort order rng = np.random.RandomState(0) scores = (-rng.rand(len(aid_pairs)) * 10).tolist() infr.graph.add_edges_from(aid_pairs) if True: edge_sample_size = 250 pop_nids = ut.unique(ibs.get_annot_nids(ut.unique(ut.flatten(aid_pairs)))) sorted_pairs = ut.sortedby(aid_pairs, scores)[::-1][0:edge_sample_size] sorted_nids = ibs.get_annot_nids(ut.take_column(sorted_pairs, 0)) sample_size = len(ut.unique(sorted_nids)) am_rowids = ibs.get_annotmatch_rowid_from_undirected_superkey(*zip(*sorted_pairs)) flags = ut.not_list(ut.flag_None_items(am_rowids)) #am_rowids = ut.compress(am_rowids, flags) positive_tags = ['SplitCase', 'Photobomb'] flags_list = [ut.replace_nones(ibs.get_annotmatch_prop(tag, am_rowids), 0) for tag in positive_tags] print('edge_case_hist: ' + ut.repr3( ['%s %s' % (txt, sum(flags_)) for flags_, txt in zip(flags_list, positive_tags)])) is_positive = ut.or_lists(*flags_list) num_positive = sum(ut.lmap(any, ut.group_items(is_positive, sorted_nids).values())) pop = len(pop_nids) print('A positive is any edge flagged as a %s' % (ut.conj_phrase(positive_tags, 'or'),)) print('--- Sampling wrt edges ---') print('edge_sample_size = %r' % (edge_sample_size,)) print('edge_population_size = %r' % (len(aid_pairs),)) print('num_positive_edges = %r' % (sum(is_positive))) print('--- Sampling wrt names ---') print('name_population_size = %r' % (pop,)) vt.calc_error_bars_from_sample(sample_size, num_positive, pop, conf_level=.95) nx.set_edge_attributes(infr.graph, name='score', values=dict(zip(aid_pairs, scores))) win = viz_graph2.AnnotGraphWidget(infr=infr, use_image=False, init_mode=None) win.populate_edge_model() win.show() return win # Make review interface for only bad edges infr_list = [] iter_ = list(zip(flagged_annots, bad_edges_list)) for annots, bad_edges in ut.ProgIter(iter_, lbl='creating inference', **progkw): aids = annots.aids nids = [1] * len(aids) infr = graph_iden.AnnotInference(ibs, aids, nids, verbose=False) infr.initialize_graph() infr.reset_feedback() infr_list.append(infr) # Check which ones are user defined as incorrect #num_positive = 0 #for infr in infr_list: # flag = np.any(infr.get_feedback_probs()[0] == 0) # num_positive += flag #print('num_positive = %r' % (num_positive,)) #pop = len(infr_list) #print('pop = %r' % (pop,)) iter_ = list(zip(infr_list, bad_edges_list)) for infr, bad_edges in ut.ProgIter(iter_, lbl='adding speed edges', **progkw): flipped_edges = [] for aid1, aid2 in bad_edges: if infr.graph.has_edge(aid1, aid2): flipped_edges.append((aid1, aid2)) infr.add_feedback((aid1, aid2), NEGTV) nx.set_edge_attributes(infr.graph, name='_speed_split', values='orig') nx.set_edge_attributes(infr.graph, name='_speed_split', values={edge: 'new' for edge in bad_edges}) nx.set_edge_attributes(infr.graph, name='_speed_split', values={edge: 'flip' for edge in flipped_edges}) #for infr in ut.ProgIter(infr_list, lbl='flagging speeding edges', **progkw): # annots = ibs.annots(infr.aids) # edge_to_speeds = annots.get_speeds() # bad_edges = [edge for edge, speed in edge_to_speeds.items() if speed > MAX_SPEED] def inference_stats(infr_list_): relabel_stats = [] for infr in infr_list_: num_ccs, num_inconsistent = infr.relabel_using_reviews() state_hist = ut.dict_hist(nx.get_edge_attributes(infr.graph, 'decision').values()) if POSTV not in state_hist: state_hist[POSTV] = 0 hist = ut.dict_hist(nx.get_edge_attributes(infr.graph, '_speed_split').values()) subgraphs = infr.positive_connected_compoments() subgraph_sizes = [len(g) for g in subgraphs] info = ut.odict([ ('num_nonmatch_edges', state_hist[NEGTV]), ('num_match_edges', state_hist[POSTV]), ('frac_nonmatch_edges', state_hist[NEGTV] / (state_hist[POSTV] + state_hist[NEGTV])), ('num_inconsistent', num_inconsistent), ('num_ccs', num_ccs), ('edges_flipped', hist.get('flip', 0)), ('edges_unchanged', hist.get('orig', 0)), ('bad_unreviewed_edges', hist.get('new', 0)), ('orig_size', len(infr.graph)), ('new_sizes', subgraph_sizes), ]) relabel_stats.append(info) return relabel_stats relabel_stats = inference_stats(infr_list) print('\nAll Split Info:') lines = [] for key in relabel_stats[0].keys(): data = ut.take_column(relabel_stats, key) if key == 'new_sizes': data = ut.flatten(data) lines.append('stats(%s) = %s' % (key, ut.repr2(ut.get_stats(data, use_median=True), precision=2))) print('\n'.join(ut.align_lines(lines, '='))) num_incon_list = np.array(ut.take_column(relabel_stats, 'num_inconsistent')) can_split_flags = num_incon_list == 0 print('Can trivially split %d / %d' % (sum(can_split_flags), len(can_split_flags))) splittable_infrs = ut.compress(infr_list, can_split_flags) relabel_stats = inference_stats(splittable_infrs) print('\nTrival Split Info:') lines = [] for key in relabel_stats[0].keys(): if key in ['num_inconsistent']: continue data = ut.take_column(relabel_stats, key) if key == 'new_sizes': data = ut.flatten(data) lines.append('stats(%s) = %s' % ( key, ut.repr2(ut.get_stats(data, use_median=True), precision=2))) print('\n'.join(ut.align_lines(lines, '='))) num_match_edges = np.array(ut.take_column(relabel_stats, 'num_match_edges')) num_nonmatch_edges = np.array(ut.take_column(relabel_stats, 'num_nonmatch_edges')) flags1 = np.logical_and(num_match_edges > num_nonmatch_edges, num_nonmatch_edges < 3) reasonable_infr = ut.compress(splittable_infrs, flags1) new_sizes_list = ut.take_column(relabel_stats, 'new_sizes') flags2 = [len(sizes) == 2 and sum(sizes) > 4 and (min(sizes) / max(sizes)) > .3 for sizes in new_sizes_list] reasonable_infr = ut.compress(splittable_infrs, flags2) print('#reasonable_infr = %r' % (len(reasonable_infr),)) for infr in ut.InteractiveIter(reasonable_infr): annots = ibs.annots(infr.aids) edge_to_speeds = annots.get_speeds() print('max_speed = %r' % (max(edge_to_speeds.values())),) infr.initialize_visual_node_attrs() infr.show_graph(use_image=True, only_reviewed=True) rest = ~np.logical_or(flags1, flags2) nonreasonable_infr = ut.compress(splittable_infrs, rest) rng = np.random.RandomState(0) random_idx = ut.random_indexes(len(nonreasonable_infr) - 1, 15, rng=rng) random_infr = ut.take(nonreasonable_infr, random_idx) for infr in ut.InteractiveIter(random_infr): annots = ibs.annots(infr.aids) edge_to_speeds = annots.get_speeds() print('max_speed = %r' % (max(edge_to_speeds.values())),) infr.initialize_visual_node_attrs() infr.show_graph(use_image=True, only_reviewed=True) #import scipy.stats as st #conf_interval = .95 #st.norm.cdf(conf_interval) # view-source:http://www.surveysystem.com/sscalc.htm #zval = 1.96 # 95 percent confidence #zValC = 3.8416 # #zValC = 6.6564 #import statsmodels.stats.api as sms #es = sms.proportion_effectsize(0.5, 0.75) #sms.NormalIndPower().solve_power(es, power=0.9, alpha=0.05, ratio=1) pop = 279 num_positive = 3 sample_size = 15 conf_level = .95 #conf_level = .99 vt.calc_error_bars_from_sample(sample_size, num_positive, pop, conf_level) print('---') vt.calc_error_bars_from_sample(sample_size + 38, num_positive, pop, conf_level) print('---') vt.calc_error_bars_from_sample(sample_size + 38 / 3, num_positive, pop, conf_level) print('---') vt.calc_error_bars_from_sample(15 + 38, num_positive=3, pop=675, conf_level=.95) vt.calc_error_bars_from_sample(15, num_positive=3, pop=675, conf_level=.95) pop = 279 #err_frac = .05 # 5% err_frac = .10 # 10% conf_level = .95 vt.calc_sample_from_error_bars(err_frac, pop, conf_level) pop = 675 vt.calc_sample_from_error_bars(err_frac, pop, conf_level) vt.calc_sample_from_error_bars(.05, pop, conf_level=.95, prior=.1) vt.calc_sample_from_error_bars(.05, pop, conf_level=.68, prior=.2) vt.calc_sample_from_error_bars(.10, pop, conf_level=.68) vt.calc_error_bars_from_sample(100, num_positive=5, pop=675, conf_level=.95) vt.calc_error_bars_from_sample(100, num_positive=5, pop=675, conf_level=.68)
def dans_splits(ibs): """ python -m ibeis dans_splits --show Example: >>> # DISABLE_DOCTEST GGR >>> from ibeis.other.dbinfo import * # NOQA >>> import ibeis >>> dbdir = '/media/danger/GGR/GGR-IBEIS' >>> dbdir = dbdir if ut.checkpath(dbdir) else ut.truepath('~/lev/media/danger/GGR/GGR-IBEIS') >>> ibs = ibeis.opendb(dbdir=dbdir, allow_newdir=False) >>> import guitool as gt >>> gt.ensure_qtapp() >>> win = dans_splits(ibs) >>> ut.quit_if_noshow() >>> import plottool as pt >>> gt.qtapp_loop(qwin=win) """ #pair = 9262, 932 dans_aids = [26548, 2190, 9418, 29965, 14738, 26600, 3039, 2742, 8249, 20154, 8572, 4504, 34941, 4040, 7436, 31866, 28291, 16009, 7378, 14453, 2590, 2738, 22442, 26483, 21640, 19003, 13630, 25395, 20015, 14948, 21429, 19740, 7908, 23583, 14301, 26912, 30613, 19719, 21887, 8838, 16184, 9181, 8649, 8276, 14678, 21950, 4925, 13766, 12673, 8417, 2018, 22434, 21149, 14884, 5596, 8276, 14650, 1355, 21725, 21889, 26376, 2867, 6906, 4890, 21524, 6690, 14738, 1823, 35525, 9045, 31723, 2406, 5298, 15627, 31933, 19535, 9137, 21002, 2448, 32454, 12615, 31755, 20015, 24573, 32001, 23637, 3192, 3197, 8702, 1240, 5596, 33473, 23874, 9558, 9245, 23570, 33075, 23721, 24012, 33405, 23791, 19498, 33149, 9558, 4971, 34183, 24853, 9321, 23691, 9723, 9236, 9723, 21078, 32300, 8700, 15334, 6050, 23277, 31164, 14103, 21231, 8007, 10388, 33387, 4319, 26880, 8007, 31164, 32300, 32140] is_hyrbid = [7123, 7166, 7157, 7158, ] # NOQA needs_mask = [26836, 29742] # NOQA justfine = [19862] # NOQA annots = ibs.annots(dans_aids) unique_nids = ut.unique(annots.nids) grouped_aids = ibs.get_name_aids(unique_nids) annot_groups = ibs._annot_groups(grouped_aids) split_props = {'splitcase', 'photobomb'} needs_tag = [len(split_props.intersection(ut.flatten(tags))) == 0 for tags in annot_groups.match_tags] num_needs_tag = sum(needs_tag) num_had_split = len(needs_tag) - num_needs_tag print('num_had_split = %r' % (num_had_split,)) print('num_needs_tag = %r' % (num_needs_tag,)) #all_annot_groups = ibs._annot_groups(ibs.group_annots_by_name(ibs.get_valid_aids())[0]) #all_has_split = [len(split_props.intersection(ut.flatten(tags))) > 0 for tags in all_annot_groups.match_tags] #num_nondan = sum(all_has_split) - num_had_split #print('num_nondan = %r' % (num_nondan,)) from ibeis.algo.graph import graph_iden from ibeis.viz import viz_graph2 import guitool as gt import plottool as pt pt.qt4ensure() gt.ensure_qtapp() aids_list = ut.compress(grouped_aids, needs_tag) aids_list = [a for a in aids_list if len(a) > 1] print('len(aids_list) = %r' % (len(aids_list),)) for aids in aids_list: infr = graph_iden.AnnotInference(ibs, aids) infr.initialize_graph() win = viz_graph2.AnnotGraphWidget(infr=infr, use_image=False, init_mode='rereview') win.populate_edge_model() win.show() return win assert False
print("on double click") printDBG('on_doubleclick') model = qtindex.model() id_ = model._get_row_id(qtindex) print('dblclick (%r,%r)' % (qtindex.row(), qtindex.column())) if model.name == THUMB_TABLE: # imgsetid = model.imgsetid gid = id_ if gid is None: return ibswgt.roi_interact = interact_annotations2.ANNOTATION_Interaction2( ibswgt.ibs, gid) print("DOUBLECLICKED ID: %r" % gid) if __name__ == '__main__': import ibeis import sys ibeis._preload(mpl=False, par=False) guitool.ensure_qtapp() dbdir = ibeis.sysres.get_args_dbdir(defaultdb='cache') ibs = IBEISControl.IBEISController(dbdir=dbdir) ibswgt = IBEISGuiWidget(ibs=ibs) ibswgt.resize(900, 600) if '--cmd' in sys.argv: guitool.qtapp_loop(qwin=ibswgt, ipy=True) exec(utool.ipython_execstr()) else: guitool.qtapp_loop(qwin=ibswgt)
def ggr_random_name_splits(): """ CommandLine: python -m ibeis.viz.viz_graph2 ggr_random_name_splits --show Ignore: sshfs -o idmap=user lev:/ ~/lev Example: >>> # DISABLE_DOCTEST GGR >>> from ibeis.viz.viz_graph2 import * # NOQA >>> ggr_random_name_splits() """ import guitool as gt gt.ensure_qtapp() #nid_list = ibs.get_valid_nids(filter_empty=True) import ibeis dbdir = '/media/danger/GGR/GGR-IBEIS' dbdir = dbdir if ut.checkpath(dbdir) else ut.truepath( '~/lev/media/danger/GGR/GGR-IBEIS') ibs = ibeis.opendb(dbdir=dbdir, allow_newdir=False) import datetime day1 = datetime.date(2016, 1, 30) day2 = datetime.date(2016, 1, 31) orig_filter_kw = { 'multiple': None, #'view': ['right'], #'minqual': 'good', 'is_known': True, 'min_pername': 2, } orig_aids = ibs.filter_annots_general(filter_kw=ut.dict_union( orig_filter_kw, { 'min_unixtime': ut.datetime_to_posixtime(ut.date_to_datetime(day1, 0.0)), 'max_unixtime': ut.datetime_to_posixtime(ut.date_to_datetime(day2, 1.0)), })) orig_all_annots = ibs.annots(orig_aids) orig_unique_nids, orig_grouped_annots_ = orig_all_annots.group( orig_all_annots.nids) # Ensure we get everything orig_grouped_annots = [ ibs.annots(aids_) for aids_ in ibs.get_name_aids(orig_unique_nids) ] # pip install quantumrandom if False: import quantumrandom data = quantumrandom.uint16() seed = data.sum() print('seed = %r' % (seed, )) #import Crypto.Random #from Crypto import Random #quantumrandom.get_data() #StrongRandom = Crypto.Random.random.StrongRandom #aes.reseed(3340258) #chars = [str(chr(x)) for x in data.view(np.uint8)] #aes_seed = str('').join(chars) #aes = Crypto.Random.Fortuna.FortunaGenerator.AESGenerator() #aes.reseed(aes_seed) #aes.pseudo_random_data(10) orig_rand_idxs = ut.random_indexes(len(orig_grouped_annots), seed=3340258) orig_sample_size = 75 random_annot_groups = ut.take(orig_grouped_annots, orig_rand_idxs) orig_annot_sample = random_annot_groups[:orig_sample_size] # OOOPS MADE ERROR REDO ---- filter_kw = { 'multiple': None, 'view': ['right'], 'minqual': 'good', 'is_known': True, 'min_pername': 2, } filter_kw_ = ut.dict_union( filter_kw, { 'min_unixtime': ut.datetime_to_posixtime(ut.date_to_datetime(day1, 0.0)), 'max_unixtime': ut.datetime_to_posixtime(ut.date_to_datetime(day2, 1.0)), }) refiltered_sample = [ ibs.filter_annots_general(annot.aids, filter_kw=filter_kw_) for annot in orig_annot_sample ] is_ok = (np.array(ut.lmap(len, refiltered_sample)) >= 2) ok_part_orig_sample = ut.compress(orig_annot_sample, is_ok) ok_part_orig_nids = [x.nids[0] for x in ok_part_orig_sample] # Now compute real sample aids = ibs.filter_annots_general(filter_kw=filter_kw_) all_annots = ibs.annots(aids) unique_nids, grouped_annots_ = all_annots.group(all_annots.nids) grouped_annots = grouped_annots_ # Ensure we get everything #grouped_annots = [ibs.annots(aids_) for aids_ in ibs.get_name_aids(unique_nids)] pop = len(grouped_annots) pername_list = ut.lmap(len, grouped_annots) groups = ibeis.annots.AnnotGroups(grouped_annots, ibs) match_tags = [ut.unique(ut.flatten(t)) for t in groups.match_tags] tag_case_hist = ut.dict_hist(ut.flatten(match_tags)) print('name_pop = %r' % (pop, )) print('Annots per Multiton Name' + ut.repr3(ut.get_stats(pername_list, use_median=True))) print('Name Tag Hist ' + ut.repr3(tag_case_hist)) print('Percent Photobomb: %.2f%%' % (tag_case_hist['photobomb'] / pop * 100)) print('Percent Split: %.2f%%' % (tag_case_hist['splitcase'] / pop * 100)) # Remove the ok part from this sample remain_unique_nids = ut.setdiff(unique_nids, ok_part_orig_nids) remain_grouped_annots = [ ibs.annots(aids_) for aids_ in ibs.get_name_aids(remain_unique_nids) ] sample_size = 75 import vtool as vt vt.calc_sample_from_error_bars(.05, pop, conf_level=.95, prior=.05) remain_rand_idxs = ut.random_indexes(len(remain_grouped_annots), seed=3340258) remain_sample_size = sample_size - len(ok_part_orig_nids) remain_random_annot_groups = ut.take(remain_grouped_annots, remain_rand_idxs) remain_annot_sample = remain_random_annot_groups[:remain_sample_size] annot_sample_nofilter = ok_part_orig_sample + remain_annot_sample # Filter out all bad parts annot_sample_filter = [ ibs.annots(ibs.filter_annots_general(annot.aids, filter_kw=filter_kw_)) for annot in annot_sample_nofilter ] annot_sample = annot_sample_filter win = None from ibeis.viz import viz_graph2 for annots in ut.InteractiveIter(annot_sample): if win is not None: win.close() win = viz_graph2.make_qt_graph_interface(ibs, aids=annots.aids, init_mode='rereview') print(win) sample_groups = ibeis.annots.AnnotGroups(annot_sample, ibs) flat_tags = [ut.unique(ut.flatten(t)) for t in sample_groups.match_tags] print('Using Split and Photobomb') is_positive = ['photobomb' in t or 'splitcase' in t for t in flat_tags] num_positive = sum(is_positive) vt.calc_error_bars_from_sample(sample_size, num_positive, pop, conf_level=.95) print('Only Photobomb') is_positive = ['photobomb' in t for t in flat_tags] num_positive = sum(is_positive) vt.calc_error_bars_from_sample(sample_size, num_positive, pop, conf_level=.95) print('Only SplitCase') is_positive = ['splitcase' in t for t in flat_tags] num_positive = sum(is_positive) vt.calc_error_bars_from_sample(sample_size, num_positive, pop, conf_level=.95)