def oracle_review(sim):
queue_params = {
'pos_diameter': None,
'neg_diameter': None,
}
infr = sim.infr
prev = infr.verbose
infr.verbose = 0
# rng = np.random.RandomState(0)
infr = sim.infr
primary_truth = sim.primary_truth
review_edges = infr.generate_reviews(**queue_params)
max_reviews = 1000
for count, (aid1, aid2) in enumerate(ut.ProgIter(review_edges)):
state = primary_truth.loc[(aid1, aid2)].idxmax()
tags = []
infr.add_feedback(aid1,
aid2,
state,
tags,
apply=True,
rectify=False,
user_id='oracle',
confidence='absolutely_sure')
if count > max_reviews:
break
infr.verbose = prev
sim.results['max_reviews'] = max_reviews
n_clusters, n_inconsistent = infr.relabel_using_reviews(rectify=False)
assert n_inconsistent == 0, 'should not create any inconsistencies'
sim.results['n_user_clusters'] = n_clusters
# infr.apply_review_inference()
curr_decisions = infr.edge_attr_df('decision')
curr_truth = primary_truth.loc[curr_decisions.index].idxmax(axis=1)
n_user_mistakes = curr_decisions != curr_truth
sim.results['n_user_mistakes'] = sum(n_user_mistakes)
gt_clusters = ut.group_pairs(infr.gen_node_attrs('orig_name_label'))
curr_clusters = ut.group_pairs(infr.gen_node_attrs('name_label'))
compare_results = compare_groups(list(gt_clusters.values()),
list(curr_clusters.values()))
sim.results.update(ut.map_vals(len, compare_results))
common_per_num = ut.group_items(compare_results['common'],
map(len, compare_results['common']))
sumafter = 3
greater = [i for i in common_per_num.keys() if i > sumafter]
common_per_num['>%s' % sumafter] = ut.flatten(
ut.take(common_per_num, greater))
ut.delete_keys(common_per_num, greater)
for k, v in common_per_num.items():
sim.results['common@' + str(k)] = len(v)
sim.results['n_names_common'] = len(compare_results['common'])
def print_dataset_info(data, labels, key):
labelhist = {key: len(val) for key, val in ut.group_items(labels, labels).items()}
stats_dict = ut.get_stats(data.ravel())
ut.delete_keys(stats_dict, ['shape', 'nMax', 'nMin'])
print('[dataset] Dataset Info: ')
print('[dataset] * Data:')
print('[dataset] %s_data(shape=%r, dtype=%r)' % (key, data.shape, data.dtype))
print('[dataset] %s_memory(data) = %r' % (key, ut.get_object_size_str(data),))
print('[dataset] %s_stats(data) = %s' % (key, ut.repr2(stats_dict, precision=2),))
print('[dataset] * Labels:')
print('[dataset] %s_labels(shape=%r, dtype=%r)' % (key, labels.shape, labels.dtype))
print('[dataset] %s_label histogram = %s' % (key, ut.repr2(labelhist)))
def check_baseline_results(sim):
import networkx as nx
infr = sim.infr
n_names_possible = 0
real_groups = ut.group_pairs(infr.gen_node_attrs('orig_name_label'))
possible_clusters = []
for nid, nodes in real_groups.items():
if len(nodes) == 1:
possible_clusters.append(nodes)
n_names_possible += 1
continue
cc_cand_edges = list(ut.nx_edges_between(infr.graph, nodes))
cc = ut.nx_from_node_edge(nodes, cc_cand_edges)
mst = nx.minimum_spanning_tree(cc)
ccs = list(nx.connected_components(mst))
possible_clusters.extend(ccs)
n_names_possible += (len(ccs))
sumafter = 3
best_possible_compare_results = compare_groups(
list(real_groups.values()), list(possible_clusters))
possible_per_num = ut.map_vals(
len,
ut.group_items(best_possible_compare_results['common'],
map(len, best_possible_compare_results['common'])))
greater = [i for i in possible_per_num.keys() if i > sumafter]
possible_per_num['>%s' % sumafter] = sum(
ut.take(possible_per_num, greater))
ut.delete_keys(possible_per_num, greater)
for k, v in possible_per_num.items():
sim.results['possible@' + str(k)] = v
sim.results['possible'] = len(best_possible_compare_results['common'])
# Measure the number of real names in the test (per number of annots)
real_per_num = ut.dict_hist(map(len, real_groups.values()))
greater = [i for i in real_per_num.keys() if i > sumafter]
real_per_num['>%s' % sumafter] = sum(ut.take(real_per_num, greater))
ut.delete_keys(real_per_num, greater)
for k, v in real_per_num.items():
sim.results['real@' + str(k)] = v
sim.results['n_names_possible'] = n_names_possible
sim.results['n_names_real'] = len(real_groups)
sim.results['real'] = len(real_groups)
def _read_raw_entries(bibman):
parser = bparser.BibTexParser()
ut.delete_keys(parser.alt_dict, ['url', 'urls'])
parser.ignore_nonstandard_types = False
text = ut.readfrom(bibman.fpath)
# ensure good format
flag = 0
for x in re.finditer('^.*}\n[^}\n]', text, flags=re.MULTILINE):
lineno = x.string[:x.start()].count('\n') + 1
print('DID YOU FORGET A COMMA ON lineno = {!r}'.format(lineno))
print(x.group())
flag += 1
assert not flag, 'fix formating'
database = parser.parse(text)
entries = database.entries
raw_entries = database.get_entry_dict()
raw_entries = ut.order_dict_by(raw_entries, [e['ID'] for e in entries])
bibman.raw_text = text
bibman.raw_entries = raw_entries
def compress_aidcfg(acfg,
filter_nones=False,
filter_empty=False,
force_noncommon=[]):
r"""
Idea is to add a third subconfig named `common` that is the intersection of
`qcfg` and `dcfg`.
Args:
acfg (dict):
Returns:
dict: acfg
CommandLine:
#python -m ibeis --tf compress_aidcfg
python -m ibeis.expt.annotation_configs --exec-compress_aidcfg --show
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.expt.annotation_configs import * # NOQA
>>> acfg = default
>>> acfg = compress_aidcfg(acfg)
>>> result = ('acfg = %s' % (ut.repr2(acfg),))
>>> print(default)
>>> print(result)
"""
import copy
if 'qcfg' not in acfg or 'dcfg' not in acfg:
return acfg
acfg = copy.deepcopy(acfg)
common_cfg = ut.dict_intersection(acfg['qcfg'], acfg['dcfg'])
ut.delete_keys(common_cfg, force_noncommon)
ut.delete_keys(acfg['qcfg'], common_cfg.keys())
ut.delete_keys(acfg['dcfg'], common_cfg.keys())
acfg['common'] = common_cfg
if filter_nones:
acfg['common'] = ut.dict_filter_nones(acfg['common'])
acfg['qcfg'] = ut.dict_filter_nones(acfg['qcfg'])
acfg['dcfg'] = ut.dict_filter_nones(acfg['dcfg'])
if filter_empty:
if len(acfg['common']) == 0:
del acfg['common']
if len(acfg['qcfg']) == 0:
del acfg['qcfg']
if len(acfg['dcfg']) == 0:
del acfg['dcfg']
return acfg
def compress_aidcfg(acfg, filter_nones=False, filter_empty=False, force_noncommon=[]):
r"""
Args:
acfg (dict):
Returns:
dict: acfg
CommandLine:
#python -m ibeis --tf compress_aidcfg
python -m ibeis.expt.annotation_configs --exec-compress_aidcfg --show
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.expt.annotation_configs import * # NOQA
>>> acfg = default
>>> acfg = compress_aidcfg(acfg)
>>> result = ('acfg = %s' % (ut.dict_str(acfg),))
>>> print(default)
>>> print(result)
"""
import copy
if 'qcfg' not in acfg or 'dcfg' not in acfg:
return acfg
acfg = copy.deepcopy(acfg)
common_cfg = ut.dict_intersection(acfg['qcfg'], acfg['dcfg'])
ut.delete_keys(common_cfg, force_noncommon)
ut.delete_keys(acfg['qcfg'], common_cfg.keys())
ut.delete_keys(acfg['dcfg'], common_cfg.keys())
acfg['common'] = common_cfg
if filter_nones:
acfg['common'] = ut.dict_filter_nones(acfg['common'])
acfg['qcfg'] = ut.dict_filter_nones(acfg['qcfg'])
acfg['dcfg'] = ut.dict_filter_nones(acfg['dcfg'])
if filter_empty:
if len(acfg['common']) == 0:
del acfg['common']
if len(acfg['qcfg']) == 0:
del acfg['qcfg']
if len(acfg['dcfg']) == 0:
del acfg['dcfg']
return acfg
def show_matches2(ibs,
aid1,
aid2,
fm=None,
fs=None,
fm_norm=None,
sel_fm=[],
H1=None,
H2=None,
qreq_=None,
**kwargs):
"""
TODO: DEPRICATE and use special case of show_name_matches
Integrate ChipMatch
Used in:
Found 1 line(s) in '/home/joncrall/code/ibeis_cnn/ibeis_cnn/ingest_ibeis.py':
ingest_ibeis.py : 827 | >>> ibeis.viz.viz_matches.show_matches2(ibs, aid1, aid2, fm=None, kpts1=kpts1, kpts2=kpts2)
----------------------
Found 4 line(s) in '/home/joncrall/code/ibeis/ibeis/viz/viz_matches.py':
viz_matches.py : 423 |def show_matches2(ibs, aid1, aid2, fm=None, fs=None, fm_norm=None, sel_fm=[],
viz_matches.py : 430 | python -m ibeis.viz.viz_matches --exec-show_matches2 --show
viz_matches.py : 431 | python -m ibeis --tf ChipMatch.ishow_single_annotmatch show_matches2 --show
viz_matches.py : 515 | return show_matches2(ibs, aid1, aid2, fm, fs, qreq_=qreq_, **kwargs)
----------------------
Found 1 line(s) in '/home/joncrall/code/ibeis/ibeis/viz/interact/interact_matches.py':
interact_matches.py : 372 | tup = viz.viz_matches.show_matches2(ibs, self.qaid, self.daid,
----------------------
Found 1 line(s) in '/home/joncrall/code/ibeis/ibeis/algo/hots/vsone_pipeline.py':
vsone_pipeline.py : 1339 | viz_matches.show_matches2(ibs, qaid, daid, fm=fm, fs=fs, fm_norm=fm_norm, ori=True,
----------------------
Found 2 line(s) in '/home/joncrall/code/ibeis/ibeis/algo/hots/chip_match.py':
chip_match.py : 204 | viz_matches.show_matches2(qreq_.ibs, cm.qaid, daid, qreq_=qreq_,
chip_match.py : 219 | ibeis.viz.viz_matches.show_matches2
----------------------
Found 1 line(s) in '/home/joncrall/code/ibeis/ibeis/algo/hots/scoring.py':
scoring.py : 562 | viz.viz_matches.show_matches2(qreq_.ibs, qaid, daid, fm, fs,
CommandLine:
python -m ibeis.viz.viz_matches --exec-show_matches2 --show
python -m ibeis --tf ChipMatch.ishow_single_annotmatch show_matches2 --show
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.algo.hots.chip_match import * # NOQA
>>> import ibeis
>>> cm, qreq_ = ibeis.testdata_cm(defaultdb='PZ_MTEST', default_qaids=[18])
>>> cm.score_nsum(qreq_)
>>> daid = cm.get_top_aids()[0]
>>> cm.show_single_annotmatch(qreq_, daid)
>>> ut.show_if_requested()
"""
if qreq_ is None:
print('[viz_matches] WARNING: qreq_ is None')
kwargs = kwargs.copy()
in_image = kwargs.get('in_image', False)
draw_fmatches = kwargs.pop('draw_fmatches', True)
# Read query and result info (chips, names, ...)
rchip1, rchip2, kpts1, kpts2 = _get_annot_pair_info(
ibs, aid1, aid2, qreq_, draw_fmatches, **kwargs)
ut.delete_keys(kwargs, ['kpts1', 'kpts2'])
if fm is None:
assert len(kpts1) == len(
kpts2), 'keypoints should be in correspondence'
import numpy as np
fm = np.vstack((np.arange(len(kpts1)), np.arange(len(kpts1)))).T
# Build annotation strings / colors
lbl1 = 'q' + vh.get_aidstrs(aid1)
lbl2 = vh.get_aidstrs(aid2)
if in_image: # HACK!
lbl1 = None
lbl2 = None
# Draws the chips and keypoint matches
try:
ax, xywh1, xywh2 = pt.show_chipmatch2(rchip1,
rchip2,
kpts1,
kpts2,
fm,
fs=fs,
fm_norm=fm_norm,
H1=H1,
H2=H2,
lbl1=lbl1,
lbl2=lbl2,
sel_fm=sel_fm,
**kwargs)
except Exception as ex:
ut.printex(ex, 'consider qr.remove_corrupted_queries', '[viz_matches]')
print('')
raise
# Moved the code into show_chipmatch
#if len(sel_fm) > 0:
# # Draw any selected matches
# sm_kw = dict(rect=True, colors=pt.BLUE)
# pt.plot_fmatch(xywh1, xywh2, kpts1, kpts2, sel_fm, **sm_kw)
(x1, y1, w1, h1) = xywh1
(x2, y2, w2, h2) = xywh2
offset1 = (x1, y1)
offset2 = (x2, y2)
annotate_matches2(ibs,
aid1,
aid2,
fm,
fs,
xywh2=xywh2,
xywh1=xywh1,
offset1=offset1,
offset2=offset2,
**kwargs)
return ax, xywh1, xywh2
def main(bib_fpath=None):
r"""
intro point to fixbib script
CommmandLine:
fixbib
python -m fixtex bib
python -m fixtex bib --dryrun
python -m fixtex bib --dryrun --debug
"""
if bib_fpath is None:
bib_fpath = 'My Library.bib'
# DEBUG = ub.argflag('--debug')
# Read in text and ensure ascii format
dirty_text = ut.readfrom(bib_fpath)
from fixtex.fix_tex import find_used_citations, testdata_fpaths
if exists('custom_extra.bib'):
extra_parser = bparser.BibTexParser(ignore_nonstandard_types=False)
parser = bparser.BibTexParser()
ut.delete_keys(parser.alt_dict, ['url', 'urls'])
print('Parsing extra bibtex file')
extra_text = ut.readfrom('custom_extra.bib')
extra_database = extra_parser.parse(extra_text, partial=False)
print('Finished parsing extra')
extra_dict = extra_database.get_entry_dict()
else:
extra_dict = None
#udata = dirty_text.decode("utf-8")
#dirty_text = udata.encode("ascii", "ignore")
#dirty_text = udata
# parser = bparser.BibTexParser()
# bib_database = parser.parse(dirty_text)
# d = bib_database.get_entry_dict()
print('BIBTEXPARSER LOAD')
parser = bparser.BibTexParser(ignore_nonstandard_types=False,
common_strings=True)
ut.delete_keys(parser.alt_dict, ['url', 'urls'])
print('Parsing bibtex file')
bib_database = parser.parse(dirty_text, partial=False)
print('Finished parsing')
bibtex_dict = bib_database.get_entry_dict()
old_keys = list(bibtex_dict.keys())
new_keys = []
for key in ub.ProgIter(old_keys, label='fixing keys'):
new_key = key
new_key = new_key.replace(':', '')
new_key = new_key.replace('-', '_')
new_key = re.sub('__*', '_', new_key)
new_keys.append(new_key)
# assert len(ut.find_duplicate_items(new_keys)) == 0, 'new keys created conflict'
assert len(ub.find_duplicates(new_keys)) == 0, 'new keys created conflict'
for key, new_key in zip(old_keys, new_keys):
if key != new_key:
entry = bibtex_dict[key]
entry['ID'] = new_key
bibtex_dict[new_key] = entry
del bibtex_dict[key]
# The bibtext is now clean. Print it to stdout
#print(clean_text)
verbose = None
if verbose is None:
verbose = 1
# Find citations from the tex documents
key_list = None
if key_list is None:
cacher = ub.Cacher('texcite1', enabled=0)
data = cacher.tryload()
if data is None:
fpaths = testdata_fpaths()
key_list, inverse = find_used_citations(fpaths,
return_inverse=True)
# ignore = ['JP', '?', 'hendrick']
# for item in ignore:
# try:
# key_list.remove(item)
# except ValueError:
# pass
if verbose:
print('Found %d citations used in the document' %
(len(key_list), ))
data = key_list, inverse
cacher.save(data)
key_list, inverse = data
# else:
# key_list = None
unknown_pubkeys = []
debug_author = ub.argval('--debug-author', default=None)
# ./fix_bib.py --debug_author=Kappes
if verbose:
print('Fixing %d/%d bibtex entries' %
(len(key_list), len(bibtex_dict)))
# debug = True
debug = False
if debug_author is not None:
debug = False
known_keys = list(bibtex_dict.keys())
missing_keys = set(key_list) - set(known_keys)
if extra_dict is not None:
missing_keys.difference_update(set(extra_dict.keys()))
if missing_keys:
print('The library is missing keys found in tex files %s' %
(ub.repr2(missing_keys), ))
# Search for possible typos:
candidate_typos = {}
sedlines = []
for key in missing_keys:
candidates = ut.closet_words(key, known_keys, num=3, subset=True)
if len(candidates) > 1:
top = candidates[0]
if ut.edit_distance(key, top) == 1:
# "sed -i -e 's/{}/{}/g' *.tex".format(key, top)
import os
replpaths = ' '.join(
[relpath(p, os.getcwd()) for p in inverse[key]])
sedlines.append("sed -i -e 's/{}/{}/g' {}".format(
key, top, replpaths))
candidate_typos[key] = candidates
print('Cannot find key = %r' % (key, ))
print('Did you mean? %r' % (candidates, ))
print('Quick fixes')
print('\n'.join(sedlines))
# group by file
just = max([0] + list(map(len, missing_keys)))
missing_fpaths = [inverse[key] for key in missing_keys]
for fpath in sorted(set(ub.flatten(missing_fpaths))):
# ut.fix_embed_globals()
subkeys = [k for k in missing_keys if fpath in inverse[k]]
print('')
ut.cprint('--- Missing Keys ---', 'blue')
ut.cprint('fpath = %r' % (fpath, ), 'blue')
ut.cprint('{} | {}'.format('Missing'.ljust(just), 'Did you mean?'),
'blue')
for key in subkeys:
print('{} | {}'.format(ut.highlight_text(key.ljust(just), 'red'),
' '.join(candidate_typos[key])))
# for key in list(bibtex_dict.keys()):
if extra_dict is not None:
# Extra database takes precidence over regular
key_list = list(ut.unique(key_list + list(extra_dict.keys())))
for k, v in extra_dict.items():
bibtex_dict[k] = v
full = ub.argflag('--full')
for key in key_list:
try:
entry = bibtex_dict[key]
except KeyError:
continue
self = BibTexCleaner(key, entry, full=full)
if debug_author is not None:
debug = debug_author in entry.get('author', '')
if debug:
ut.cprint(' --- ENTRY ---', 'yellow')
print(ub.repr2(entry, nl=1))
entry = self.fix()
# self.clip_abstract()
# self.shorten_keys()
# self.fix_authors()
# self.fix_year()
# old_pubval = self.fix_pubkey()
# if old_pubval:
# unknown_pubkeys.append(old_pubval)
# self.fix_arxiv()
# self.fix_general()
# self.fix_paper_types()
if debug:
print(ub.repr2(entry, nl=1))
ut.cprint(' --- END ENTRY ---', 'yellow')
bibtex_dict[key] = entry
unwanted_keys = set(bibtex_dict.keys()) - set(key_list)
if verbose:
print('Removing unwanted %d entries' % (len(unwanted_keys)))
ut.delete_dict_keys(bibtex_dict, unwanted_keys)
if 0:
d1 = bibtex_dict.copy()
full = True
for key, entry in d1.items():
self = BibTexCleaner(key, entry, full=full)
pub = self.publication()
if pub is None:
print(self.entry['ENTRYTYPE'])
old = self.fix_pubkey()
x1 = self._pubval()
x2 = self.standard_pubval(full=full)
# if x2 is not None and len(x2) > 5:
# print(ub.repr2(self.entry))
if x1 != x2:
print('x2 = %r' % (x2, ))
print('x1 = %r' % (x1, ))
print(ub.repr2(self.entry))
# if 'CVPR' in self.entry.get('booktitle', ''):
# if 'CVPR' != self.entry.get('booktitle', ''):
# break
if old:
print('old = %r' % (old, ))
d1[key] = self.entry
if full:
d1 = bibtex_dict.copy()
import numpy as np
import pandas as pd
df = pd.DataFrame.from_dict(d1, orient='index')
paged_items = df[~pd.isnull(df['pub_accro'])]
has_pages = ~pd.isnull(paged_items['pages'])
print('have pages {} / {}'.format(has_pages.sum(), len(has_pages)))
print(ub.repr2(paged_items[~has_pages]['title'].values.tolist()))
entrytypes = dict(list(df.groupby('pub_type')))
if False:
# entrytypes['misc']
g = entrytypes['online']
g = g[g.columns[~np.all(pd.isnull(g), axis=0)]]
entrytypes['book']
entrytypes['thesis']
g = entrytypes['article']
g = entrytypes['incollection']
g = entrytypes['conference']
def lookup_pub(e):
if e == 'article':
return 'journal', 'journal'
elif e == 'incollection':
return 'booksection', 'booktitle'
elif e == 'conference':
return 'conference', 'booktitle'
return None, None
for e, g in entrytypes.items():
print('e = %r' % (e, ))
g = g[g.columns[~np.all(pd.isnull(g), axis=0)]]
if 'pub_full' in g.columns:
place_title = g['pub_full'].tolist()
print(ub.repr2(ub.dict_hist(place_title)))
else:
print('Unknown publications')
if 'report' in entrytypes:
g = entrytypes['report']
missing = g[pd.isnull(g['title'])]
if len(missing):
print('Missing Title')
print(ub.repr2(missing[['title', 'author']].values.tolist()))
if 'journal' in entrytypes:
g = entrytypes['journal']
g = g[g.columns[~np.all(pd.isnull(g), axis=0)]]
missing = g[pd.isnull(g['journal'])]
if len(missing):
print('Missing Journal')
print(ub.repr2(missing[['title', 'author']].values.tolist()))
if 'conference' in entrytypes:
g = entrytypes['conference']
g = g[g.columns[~np.all(pd.isnull(g), axis=0)]]
missing = g[pd.isnull(g['booktitle'])]
if len(missing):
print('Missing Booktitle')
print(ub.repr2(missing[['title', 'author']].values.tolist()))
if 'incollection' in entrytypes:
g = entrytypes['incollection']
g = g[g.columns[~np.all(pd.isnull(g), axis=0)]]
missing = g[pd.isnull(g['booktitle'])]
if len(missing):
print('Missing Booktitle')
print(ub.repr2(missing[['title', 'author']].values.tolist()))
if 'thesis' in entrytypes:
g = entrytypes['thesis']
g = g[g.columns[~np.all(pd.isnull(g), axis=0)]]
missing = g[pd.isnull(g['institution'])]
if len(missing):
print('Missing Institution')
print(ub.repr2(missing[['title', 'author']].values.tolist()))
# import utool
# utool.embed()
# Overwrite BibDatabase structure
bib_database._entries_dict = bibtex_dict
bib_database.entries = list(bibtex_dict.values())
#conftitle_to_types_set_hist = {key: set(val) for key, val in conftitle_to_types_hist.items()}
#print(ub.repr2(conftitle_to_types_set_hist))
print('Unknown conference keys:')
print(ub.repr2(sorted(unknown_pubkeys)))
print('len(unknown_pubkeys) = %r' % (len(unknown_pubkeys), ))
writer = BibTexWriter()
writer.contents = ['comments', 'entries']
writer.indent = ' '
writer.order_entries_by = ('type', 'author', 'year')
new_bibtex_str = bibtexparser.dumps(bib_database, writer)
# Need to check
#jegou_aggregating_2012
# Fix the Journal Abreviations
# References:
# https://www.ieee.org/documents/trans_journal_names.pdf
# Write out clean bibfile in ascii format
clean_bib_fpath = ub.augpath(bib_fpath.replace(' ', '_'), suffix='_clean')
if not ub.argflag('--dryrun'):
ut.writeto(clean_bib_fpath, new_bibtex_str)
def show_matches2(ibs, aid1, aid2, fm=None, fs=None, fm_norm=None, sel_fm=[],
H1=None, H2=None, qreq_=None, **kwargs):
"""
TODO: DEPRICATE and use special case of show_name_matches
Integrate ChipMatch
Used in:
Found 1 line(s) in '/home/joncrall/code/ibeis_cnn/ibeis_cnn/ingest_ibeis.py':
ingest_ibeis.py : 827 | >>> ibeis.viz.viz_matches.show_matches2(ibs, aid1, aid2, fm=None, kpts1=kpts1, kpts2=kpts2)
----------------------
Found 4 line(s) in '/home/joncrall/code/ibeis/ibeis/viz/viz_matches.py':
viz_matches.py : 423 |def show_matches2(ibs, aid1, aid2, fm=None, fs=None, fm_norm=None, sel_fm=[],
viz_matches.py : 430 | python -m ibeis.viz.viz_matches --exec-show_matches2 --show
viz_matches.py : 431 | python -m ibeis --tf ChipMatch.ishow_single_annotmatch show_matches2 --show
viz_matches.py : 515 | return show_matches2(ibs, aid1, aid2, fm, fs, qreq_=qreq_, **kwargs)
----------------------
Found 1 line(s) in '/home/joncrall/code/ibeis/ibeis/viz/interact/interact_matches.py':
interact_matches.py : 372 | tup = viz.viz_matches.show_matches2(ibs, self.qaid, self.daid,
----------------------
Found 1 line(s) in '/home/joncrall/code/ibeis/ibeis/algo/hots/vsone_pipeline.py':
vsone_pipeline.py : 1339 | viz_matches.show_matches2(ibs, qaid, daid, fm=fm, fs=fs, fm_norm=fm_norm, ori=True,
----------------------
Found 2 line(s) in '/home/joncrall/code/ibeis/ibeis/algo/hots/chip_match.py':
chip_match.py : 204 | viz_matches.show_matches2(qreq_.ibs, cm.qaid, daid, qreq_=qreq_,
chip_match.py : 219 | ibeis.viz.viz_matches.show_matches2
----------------------
Found 1 line(s) in '/home/joncrall/code/ibeis/ibeis/algo/hots/scoring.py':
scoring.py : 562 | viz.viz_matches.show_matches2(qreq_.ibs, qaid, daid, fm, fs,
CommandLine:
python -m ibeis.viz.viz_matches --exec-show_matches2 --show
python -m ibeis --tf ChipMatch.ishow_single_annotmatch show_matches2 --show
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.algo.hots.chip_match import * # NOQA
>>> import ibeis
>>> cm, qreq_ = ibeis.testdata_cm(defaultdb='PZ_MTEST', default_qaids=[18])
>>> cm.score_nsum(qreq_)
>>> daid = cm.get_top_aids()[0]
>>> cm.show_single_annotmatch(qreq_, daid)
>>> ut.show_if_requested()
"""
if qreq_ is None:
print('[viz_matches] WARNING: qreq_ is None')
kwargs = kwargs.copy()
in_image = kwargs.get('in_image', False)
draw_fmatches = kwargs.pop('draw_fmatches', True)
# Read query and result info (chips, names, ...)
rchip1, rchip2, kpts1, kpts2 = _get_annot_pair_info(ibs, aid1, aid2, qreq_,
draw_fmatches, **kwargs)
ut.delete_keys(kwargs, ['kpts1', 'kpts2'])
if fm is None:
assert len(kpts1) == len(kpts2), 'keypoints should be in correspondence'
import numpy as np
fm = np.vstack((np.arange(len(kpts1)), np.arange(len(kpts1)))).T
# Build annotation strings / colors
lbl1 = 'q' + vh.get_aidstrs(aid1)
lbl2 = vh.get_aidstrs(aid2)
if in_image: # HACK!
lbl1 = None
lbl2 = None
# Draws the chips and keypoint matches
try:
ax, xywh1, xywh2 = pt.show_chipmatch2(rchip1, rchip2, kpts1, kpts2, fm,
fs=fs, fm_norm=fm_norm,
H1=H1, H2=H2, lbl1=lbl1,
lbl2=lbl2, sel_fm=sel_fm,
**kwargs)
except Exception as ex:
ut.printex(ex, 'consider qr.remove_corrupted_queries',
'[viz_matches]')
print('')
raise
# Moved the code into show_chipmatch
#if len(sel_fm) > 0:
# # Draw any selected matches
# sm_kw = dict(rect=True, colors=pt.BLUE)
# pt.plot_fmatch(xywh1, xywh2, kpts1, kpts2, sel_fm, **sm_kw)
(x1, y1, w1, h1) = xywh1
(x2, y2, w2, h2) = xywh2
offset1 = (x1, y1)
offset2 = (x2, y2)
annotate_matches2(ibs, aid1, aid2, fm, fs, xywh2=xywh2, xywh1=xywh1,
offset1=offset1, offset2=offset2, **kwargs)
return ax, xywh1, xywh2
