Source code for ibeis.model.hots.smk.smk_match

# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
#import six
from six.moves import zip, range, map  # NOQA
import utool
import numpy as np
from ibeis.model.hots.smk import smk_index
from ibeis.model.hots.smk import smk_repr
from ibeis.model.hots.smk import smk_core
#from six.moves import zip
#from ibeis.model.hots.hstypes import INTEGER_TYPE
(print, print_, printDBG, rrr, profile) = utool.inject(__name__, '[smk_match]')


DEBUG_SMK = utool.DEBUG2 or utool.get_argflag('--debug-smk')


@utool.indent_func('[smk_query]')
#@utool.memprof
@profile
[docs]def execute_smk_L5(qreq_): """ ibeis query interface Example: >>> from ibeis.model.hots.smk.smk_match import * # NOQA >>> from ibeis.model.hots.smk import smk_match >>> from ibeis.model.hots.smk import smk_debug >>> ibs, annots_df, daids, qaids, invindex, qreq_ = smk_debug.testdata_internals_full() >>> qaid2_scores, qaid2_chipmatch = smk_match.execute_smk_L5(qreq_) Dev:: from ibeis.model.hots import pipeline filt2_meta = {} # Get both spatial verified and not qaid2_chipmatch_FILT_ = qaid2_chipmatch qaid2_chipmatch_SVER_ = pipeline.spatial_verification(qaid2_chipmatch_FILT_, qreq_) qaid2_qres_FILT_ = pipeline.chipmatch_to_resdict(qaid2_chipmatch_FILT_, filt2_meta, qreq_) qaid2_qres_SVER_ = pipeline.chipmatch_to_resdict(qaid2_chipmatch_SVER_, filt2_meta, qreq_) qres_FILT = qaid2_qres_FILT_[qaids[0]] qres_SVER = qaid2_qres_SVER_[qaids[0]] fig1 = qres_FILT.show_top(ibs, fnum=1, figtitle='filt') fig2 = qres_SVER.show_top(ibs, fnum=2, figtitle='sver') fig1.show() fig2.show() CommandLine:: python -m memory_profiler dev.py --db PZ_Mothers -t smk2 --allgt --index 0 python dev.py -t smk2 --allgt --db GZ_ALL python dev.py -t smk2 --allgt --db GZ_ALL python dev.py -t smk2 --allgt --db GZ_ALL --index 2:10 --vf --va python dev.py -t smk2 --allgt --db GZ_ALL --index 2:10 --vf --va --print-cfgstr python dev.py -t smk2 --allgt --db GZ_ALL --index 2:20 --vf --va python dev.py -t smk2 --allgt --db GZ_ALL --noqcache --index 2:20 --va --vf python dev.py -t smk2 --allgt --db PZ_Master0 && python dev.py -t smk3 --allgt --db PZ_Master0 python dev.py -t smk2 --allgt --db PZ_Master0 --index 2:10 --va python dev.py -t smk2 --allgt --db PZ_Mothers --index 20:30 python dev.py -t smk2 --allgt --db PZ_Mothers --noqcache --index 18:20 --super-strict --va python dev.py -t smk2 --db PZ_Master0 --qaid 7199 --va --quality --vf --noqcache python dev.py -t smk3 --allgt --db GZ_ALL --index 2:10 --vf --va python dev.py -t smk5 --allgt --db PZ_Master0 --noqcache ; python dev.py -t smk5 --allgt --db GZ_ALL --noqcache python dev.py -t smkd --allgt --db PZ_Mothers --index 1:3 --va --quality --vf --noqcache python dev.py -t smk_8k --allgt --db PZ_Mothers --index 20:30 --va --vf python dev.py -t smk_8k --allgt --db PZ_Mothers --index 20:30 --echo-hardcase python dev.py -t smk_8k --allgt --db PZ_Mothers --index 20:30 --vh python dev.py -t smk_8k_compare --allgt --db PZ_Mothers --index 20:30 --view-hard """ memtrack = utool.MemoryTracker('[SMK ENTRY]') qaids = qreq_.get_external_qaids() ibs = qreq_.ibs # Params qparams = qreq_.qparams memtrack.report('[SMK PREINIT]') # Build ~~Pandas~~ dataframe (or maybe not) annots_df = smk_repr.make_annot_df(ibs) words, invindex = prepare_qreq(qreq_, annots_df, memtrack) withinfo = True # Execute smk for each query memtrack.report('[SMK QREQ INITIALIZED]') print('[SMK_MEM] invindex is using ' + utool.get_object_size_str(invindex)) print('[SMK_MEM] qreq_ is using ' + utool.get_object_size_str(qreq_)) if utool.DEBUG2: from ibeis.model.hots.smk import smk_debug smk_debug.invindex_dbgstr(invindex) qaid2_scores, qaid2_chipmatch = execute_smk_L4(annots_df, qaids, invindex, qparams, withinfo) memtrack.report('[SMK QREQ FINISHED]') return qaid2_scores, qaid2_chipmatch #@utool.memprof
[docs]def prepare_qreq(qreq_, annots_df, memtrack): """ Called if pipeline did not setup qreq correctly """ print('\n\n+--- QREQ NEEDS TO LOAD VOCAB --- ') if hasattr(qreq_, 'words'): # Hack raise NotImplementedError('pipeline still isnt fully ready for smk') words = qreq_.words invindex = qreq_.invindex else: # Load vocabulary qparams = qreq_.qparams daids = qreq_.get_external_daids() words = smk_index.learn_visual_words(annots_df, qreq_, memtrack=memtrack) memtrack.report('[SMK LEARN VWORDS]') # Index database annotations with_internals = True invindex = smk_repr.index_data_annots(annots_df, daids, words, qparams, with_internals, memtrack) memtrack.report('[SMK INDEX ANNOTS]') print('L___ FINISHED LOADING VOCAB ___\n') return words, invindex
@profile
[docs]def execute_smk_L4(annots_df, qaids, invindex, qparams, withinfo): """ Loop over execute_smk_L3 CommandLine: python dev.py -t smk --allgt --db PZ_Mothers --index 1:3 --noqcache --va --vf """ # Progress lbl = 'ASMK query: ' if qparams.aggregate else 'SMK query: ' logkw = dict(flushfreq=1, writefreq=1, with_totaltime=True, backspace=False) mark, end_ = utool.log_progress(lbl, len(qaids), **logkw) # Output qaid2_chipmatch = {} qaid2_scores = {} # Foreach query annotation for count, qaid in enumerate(qaids): mark(count) tup = execute_smk_L3(annots_df, qaid, invindex, qparams, withinfo) daid2_score, daid2_chipmatch = tup qaid2_scores[qaid] = daid2_score qaid2_chipmatch[qaid] = daid2_chipmatch #memtrack.report('[SMK SINGLE QUERY]') end_() if DEBUG_SMK: from ibeis.model.hots.smk import smk_debug smk_debug.check_qaid2_chipmatch(qaid2_chipmatch, qaids) return qaid2_scores, qaid2_chipmatch
@profile
[docs]def execute_smk_L3(annots_df, qaid, invindex, qparams, withinfo=True): """ Executes a single smk query Example: >>> from ibeis.model.hots.smk.smk_match import * # NOQA >>> from ibeis.model.hots.smk import smk_debug >>> ibs, annots_df, daids, qaids, invindex, qreq_ = smk_debug.testdata_internals_full() >>> qaid = qaids[0] >>> qparams = qreq_.qparams >>> withinfo = True >>> daid2_totalscore, daid2_chipmatch = execute_smk_L3(annots_df, qaid, invindex, qparams, withinfo) """ #from ibeis.model.hots.smk import smk_index # Get query words / residuals qindex = smk_repr.new_qindex(annots_df, qaid, invindex, qparams) # Compute match kernel for all database aids daid2_totalscore, daid2_chipmatch = smk_core.match_kernel_L2(qindex, invindex, qparams, withinfo) # 54 % # Prevent self matches allow_self_match = qparams.allow_self_match #utool.get_argflag('--self-match') if (not allow_self_match) and qaid in daid2_totalscore: # If we cannot do self-matches daid2_totalscore[qaid] = 0 daid2_chipmatch[0][qaid] = np.empty((0, 2), dtype=np.int32) daid2_chipmatch[1][qaid] = np.empty((0), dtype=np.float32) daid2_chipmatch[2][qaid] = np.empty((0), dtype=np.int32) # Build chipmatches if daid2_wx2_scoremat is not None if DEBUG_SMK: from ibeis.model.hots.smk import smk_debug smk_debug.check_daid2_chipmatch(daid2_chipmatch) return daid2_totalscore, daid2_chipmatch
if __name__ == '__main__': def main(): from ibeis.model.hots.smk import smk_debug from ibeis.model.hots.smk import smk_match from ibeis.model.hots import pipeline ibs, taids, daids, qaids, qreq_ = smk_debug.testdata_ibeis2() qaid2_scores, qaid2_chipmatch = smk_match.execute_smk_L5(qreq_) filt2_meta = {} qaid2_qres_ = pipeline.chipmatch_to_resdict(qaid2_chipmatch, filt2_meta, qreq_) qres = qaid2_qres_[qaids[0]] fig = qres.show_top(ibs) fig.show() main() from plottool import draw_func2 as df2 exec(df2.present())