def old_test_single_annot_distinctiveness_params(ibs, aid):
r"""
CommandLine:
python -m ibeis.model.hots.distinctiveness_normalizer --test-old_test_single_annot_distinctiveness_params --show
python -m ibeis.model.hots.distinctiveness_normalizer --test-old_test_single_annot_distinctiveness_params --show --db GZ_ALL
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.model.hots.distinctiveness_normalizer import * # NOQA
>>> import plottool as pt
>>> import ibeis
>>> # build test data
>>> ibs = ibeis.opendb(ut.get_argval('--db', type_=str, default='PZ_MTEST'))
>>> aid = ut.get_argval('--aid', type_=int, default=1)
>>> # execute function
>>> old_test_single_annot_distinctiveness_params(ibs, aid)
>>> pt.show_if_requested()
"""
####
# TODO: Also paramatarize the downweighting based on the keypoint size
####
# HACK IN ABILITY TO SET CONFIG
from ibeis.dev.main_commands import postload_commands
postload_commands(ibs, None)
from vtool import coverage_image
import plottool as pt
from plottool import interact_impaint
#cfglbl_list = cfgdict_list
#ut.all_dict_combinations_lbls(varied_dict)
# Get info to find distinctivness of
species_text = ibs.get_annot_species(aid)
vecs = ibs.get_annot_vecs(aid)
kpts = ibs.get_annot_kpts(aid)
print(kpts)
chip = ibs.get_annot_chips(aid)
chipsize = ibs.get_annot_chipsizes(aid)
# Paramater space to search
# TODO: use slicing to control the params being varied
# Use GridSearch class to modify paramaters as you go.
gauss_patch_varydict = {
'gauss_shape': [(7, 7), (19, 19), (41, 41), (5, 5), (3, 3)],
'gauss_sigma_frac': [.2, .5, .7, .95],
}
cov_blur_varydict = {
'cov_blur_on': [True, False],
'cov_blur_ksize': [(5, 5,), (7, 7), (17, 17)],
'cov_blur_sigma': [5.0, 1.2],
}
dstncvs_varydict = {
'dcvs_power': [.01, .1, .5, 1.0],
'dcvs_clip_max': [.05, .1, .2, .5],
'dcvs_K': [2, 3, 5],
}
size_penalty_varydict = {
'remove_affine_information': [False, True],
'constant_scaling': [False, True],
'size_penalty_on': [True, False],
'size_penalty_power': [.5, .1, 1.0],
'size_penalty_scale': [.1, 1.0],
}
keyval_iter = ut.iflatten([
dstncvs_varydict.items(),
gauss_patch_varydict.items(),
cov_blur_varydict.items(),
size_penalty_varydict.items(),
])
# Dont vary most paramaters, specify how much of their list can be used
param_slice_dict = {
'dcvs_power' : slice(0, 2),
'dcvs_K' : slice(0, 2),
'dcvs_clip_max' : slice(0, 2),
'dcvs_clip_max' : slice(0, 2),
#'gauss_shape' : slice(0, 3),
'gauss_sigma_frac' : slice(0, 2),
'remove_affine_information' : slice(0, 2),
'constant_scaling' : slice(0, 2),
'size_penalty_on' : slice(0, 2),
#'cov_blur_on' : slice(0, 2),
#'cov_blur_ksize' : slice(0, 2),
#'cov_blur_sigma' : slice(0, 1),
#'size_penalty_power' : slice(0, 2),
#'size_penalty_scale' : slice(0, 2),
}
varied_dict = {
key: val[param_slice_dict.get(key, slice(0, 1))]
for key, val in keyval_iter
}
def constrain_config(cfg):
""" encode what makes a configuration feasible """
if cfg['cov_blur_on'] is False:
cfg['cov_blur_ksize'] = None
cfg['cov_blur_sigma'] = None
if cfg['constant_scaling'] is True:
cfg['remove_affine_information'] = True
cfg['size_penalty_on'] = False
if cfg['remove_affine_information'] is True:
cfg['gauss_shape'] = (41, 41)
if cfg['size_penalty_on'] is False:
cfg['size_penalty_power'] = None
cfg['size_penalty_scale'] = None
print('Varied Dict: ')
print(ut.dict_str(varied_dict))
cfgdict_list, cfglbl_list = ut.make_constrained_cfg_and_lbl_list(varied_dict, constrain_config)
# Get groundtruthish distinctivness map
# for objective function
GT_IS_DSTNCVS = 255
GT_NOT_DSTNCVS = 100
GT_UNKNOWN = 0
label_colors = [GT_IS_DSTNCVS, GT_NOT_DSTNCVS, GT_UNKNOWN]
gtmask = interact_impaint.cached_impaint(chip, 'dstncvnss',
label_colors=label_colors,
aug=True, refine=ut.get_argflag('--refine'))
true_dstncvs_mask = gtmask == GT_IS_DSTNCVS
false_dstncvs_mask = gtmask == GT_NOT_DSTNCVS
true_dstncvs_mask_sum = true_dstncvs_mask.sum()
false_dstncvs_mask_sum = false_dstncvs_mask.sum()
def distinctiveness_objective_function(dstncvs_mask):
true_mask = true_dstncvs_mask * dstncvs_mask
false_mask = false_dstncvs_mask * dstncvs_mask
true_score = true_mask.sum() / true_dstncvs_mask_sum
false_score = false_mask.sum() / false_dstncvs_mask_sum
score = true_score * (1 - false_score)
return score
# Load distinctivness normalizer
with ut.Timer('Loading Distinctivness Normalizer for %s' % (species_text)):
dstcvnss_normer = request_species_distinctiveness_normalizer(species_text)
# Get distinctivness over all params
dstncvs_list = [dstcvnss_normer.get_distinctiveness(vecs, **cfgdict)
for cfgdict in ut.ProgressIter(cfgdict_list, lbl='get dstcvns')]
# Then compute the distinctinvess coverage map
#gauss_shape = kwargs.get('gauss_shape', (19, 19))
#sigma_frac = kwargs.get('sigma_frac', .3)
dstncvs_mask_list = [
coverage_image.make_coverage_mask(
kpts, chipsize, fx2_score=dstncvs, mode='max', return_patch=False, **cfg)
for cfg, dstncvs in ut.ProgressIter(zip(cfgdict_list, dstncvs_list), lbl='Warping Image')
]
score_list = [distinctiveness_objective_function(dstncvs_mask) for dstncvs_mask in dstncvs_mask_list]
fnum = 1
def show_covimg_result(img, fnum=None, pnum=None):
pt.imshow(255 * img, fnum=fnum, pnum=pnum)
ut.interact_gridsearch_result_images(
show_covimg_result, cfgdict_list, cfglbl_list, dstncvs_mask_list,
score_list=score_list, fnum=fnum, figtitle='dstncvs gridsearch')
# Show subcomponents of grid search
gauss_patch_cfgdict_list, gauss_patch_cfglbl_list = ut.get_cfgdict_lbl_list_subset(cfgdict_list, gauss_patch_varydict)
patch_list = [coverage_image.get_gaussian_weight_patch(**cfgdict)
for cfgdict in ut.ProgressIter(gauss_patch_cfgdict_list, lbl='patch cfg')]
ut.interact_gridsearch_result_images(
show_covimg_result, gauss_patch_cfgdict_list, gauss_patch_cfglbl_list,
patch_list, fnum=fnum + 1, figtitle='gaussian patches')
patch = patch_list[0]
# Show the first mask in more depth
dstncvs = dstncvs_list[0]
dstncvs_mask = dstncvs_mask_list[0]
coverage_image.show_coverage_map(chip, dstncvs_mask, patch, kpts, fnum=fnum + 2, ell_alpha=.2, show_mask_kpts=False)
pt.imshow(gtmask, fnum=fnum + 3, pnum=(1, 2, 1), title='ground truth distinctiveness')
pt.imshow(chip, fnum=fnum + 3, pnum=(1, 2, 2))
pt.present()
def devmain():
"""
The Developer Script
A command line interface to almost everything
-w # wait / show the gui / figures are visible
--cmd # ipython shell to play with variables
-t # run list of tests
Examples:
"""
helpstr = ut.codeblock(
'''
Dev is meant to be run as an interactive script.
The dev.py script runs any test you regiter with @devcmd in any combination
of configurations specified by a Config object.
Dev caches information in order to get quicker results. # FIXME: Provide quicker results # FIXME: len(line)
''')
INTRO_TITLE = 'The dev.py Script'
#INTRO_TEXT = ''.join((ut.bubbletext(INTRO_TITLE, font='cybermedium'), helpstr))
INTRO_TEXT = ut.bubbletext(INTRO_TITLE, font='cybermedium')
INTRO_STR = ut.msgblock('dev.py Intro', INTRO_TEXT)
EXAMPLE_STR = ut.msgblock('dev.py Examples', ut.codeblock(EXAMPLE_TEXT))
if ut.NOT_QUIET:
print(INTRO_STR)
if ut.get_argflag(('--help', '--verbose')):
print(EXAMPLE_STR)
CMD = ut.get_argflag('--cmd')
NOGUI = not ut.get_argflag('--gui')
if len(sys.argv) == 1:
print('Run dev.py with arguments!')
sys.exit(1)
# Run Precommands
run_devprecmds()
#
#
# Run IBEIS Main, create controller, and possibly gui
print('++dev')
main_locals = ibeis.main(gui=ut.get_argflag('--gui'))
#utool.set_process_title('IBEIS_dev')
#
#
# Load snippet variables
SNIPPITS = True and CMD
if SNIPPITS:
snippet_locals = dev_snippets(main_locals)
snippet_execstr = utool.execstr_dict(snippet_locals, 'snippet_locals')
exec(snippet_execstr)
#
#
# Development code
RUN_DEV = True # RUN_DEV = '__IPYTHON__' in vars()
if RUN_DEV:
dev_locals = run_dev(main_locals['ibs'])
dev_execstr = utool.execstr_dict(dev_locals, 'dev_locals')
exec(dev_execstr)
command = ut.get_argval('--eval', type_=str, default=None)
if command is not None:
result = eval(command, globals(), locals())
print('result = %r' % (result,))
#ibs.search_annot_notes('360')
#
#
# Main Loop (IPython interaction, or some exec loop)
#if '--nopresent' not in sys.argv or '--noshow' in sys.argv:
ut.show_if_requested()
if ut.get_argflag(('--show', '--wshow')):
pt.present()
main_execstr = ibeis.main_loop(main_locals, ipy=(NOGUI or CMD))
exec(main_execstr)
#
#
# Memory profile
if ut.get_argflag('--memprof'):
utool.print_resource_usage()
utool.memory_profile()
print('exiting dev')
# # gf_rank = np.nonzero(is_negative)[0][0:num_false]
# # tn_nscores.extend(sorted_nscores[gf_rank])
# # tp_nscores = np.array(tp_nscores).astype(np.float64)
# # tn_nscores = np.array(tn_nscores).astype(np.float64)
# # return tp_nscores, tn_nscores
# #tp_nscores, tn_nscores = get_labeled_name_scores(ibs, qres_list)
#from ibeis.model.hots import score_normalization
#tp_support, tn_support, tp_support_labels, tn_support_labels = score_normalization.get_ibeis_score_training_data(ibs, qaid_list, qres_list)
#ut.embed()
#x_data, y_data = results_all.get_stem_data(ibs, qaid2_qres)
#pt.plots.plot_stems(x_data, y_data)
#pt.present()
#pt.show()
#locals_ = viz_allres_annotation_scores(allres)
if __name__ == '__main__':
"""
CommandLine:
python -c "import utool, ibeis.expt.results_all; utool.doctest_funcs(ibeis.expt.results_all, allexamples=True)"
python -c "import utool, ibeis.expt.results_all; utool.doctest_funcs(ibeis.expt.results_all)"
python -m ibeis.expt.results_all --allexamples
python -m ibeis.expt.results_all --test-learn_score_normalization --enableall
"""
import multiprocessing
multiprocessing.freeze_support() # for win32
import utool as ut # NOQA
ut.doctest_funcs()
import plottool as pt # NOQA
exec(pt.present())
def test_single_annot_distinctiveness_params(ibs, aid):
r"""
CommandLine:
python -m ibeis.algo.hots.distinctiveness_normalizer --test-test_single_annot_distinctiveness_params --show
python -m ibeis.algo.hots.distinctiveness_normalizer --test-test_single_annot_distinctiveness_params --show --db GZ_ALL
Example:
>>> # DISABLE_DOCTEST
>>> from ibeis.algo.hots.distinctiveness_normalizer import * # NOQA
>>> import plottool as pt
>>> import ibeis
>>> # build test data
>>> ibs = ibeis.opendb(ut.get_argval('--db', type_=str, default='PZ_MTEST'))
>>> aid = ut.get_argval('--aid', type_=int, default=1)
>>> # execute function
>>> test_single_annot_distinctiveness_params(ibs, aid)
>>> pt.show_if_requested()
"""
####
# TODO: Also paramatarize the downweighting based on the keypoint size
####
# HACK IN ABILITY TO SET CONFIG
from ibeis.init.main_commands import postload_commands
from ibeis.algo import Config
postload_commands(ibs, None)
import plottool as pt
#cfglbl_list = cfgdict_list
#ut.all_dict_combinations_lbls(varied_dict)
# Get info to find distinctivness of
species_text = ibs.get_annot_species(aid)
# FIXME; qreq_ params for config rowid
vecs = ibs.get_annot_vecs(aid)
kpts = ibs.get_annot_kpts(aid)
chip = ibs.get_annot_chips(aid)
# Paramater space to search
# TODO: use slicing to control the params being varied
# Use GridSearch class to modify paramaters as you go.
varied_dict = Config.DCVS_DEFAULT.get_varydict()
print('Varied Dict: ')
print(ut.dict_str(varied_dict))
cfgdict_list, cfglbl_list = ut.make_constrained_cfg_and_lbl_list(varied_dict)
# Get groundtruthish distinctivness map
# for objective function
# Load distinctivness normalizer
with ut.Timer('Loading Distinctivness Normalizer for %s' % (species_text)):
dstcvnss_normer = request_species_distinctiveness_normalizer(species_text)
# Get distinctivness over all params
dstncvs_list = [dstcvnss_normer.get_distinctiveness(vecs, **cfgdict)
for cfgdict in ut.ProgIter(cfgdict_list, lbl='get dstcvns')]
#fgweights = ibs.get_annot_fgweights([aid])[0]
#dstncvs_list = [x * fgweights for x in dstncvs_list]
fnum = 1
import functools
show_func = functools.partial(show_chip_distinctiveness_plot, chip, kpts)
ut.interact_gridsearch_result_images(
show_func, cfgdict_list, cfglbl_list, dstncvs_list,
score_list=None, fnum=fnum, figtitle='dstncvs gridsearch')
pt.present()
def devfunc(ibs, qaid_list):
""" Function for developing something """
print('[dev] devfunc')
import ibeis # NOQA
from ibeis.algo import Config # NOQA
#from ibeis.algo.Config import * # NOQA
feat_cfg = Config.FeatureConfig()
#feat_cfg.printme3()
print('\ncfgstr..')
print(feat_cfg.get_cfgstr())
print(utool.dict_str(feat_cfg.get_hesaff_params()))
from ibeis import viz
aid = 1
ibs.cfg.feat_cfg.threshold = 16.0 / 3.0
kpts = ibs.get_annot_kpts(aid)
print('len(kpts) = %r' % len(kpts))
from ibeis.expt import experiment_configs
#varyparams_list = [
# #{
# # 'threshold': [16.0 / 3.0, 32.0 / 3.0], # 8.0 / 3.0
# # 'numberOfScales': [3, 2, 1],
# # 'maxIterations': [16, 32],
# # 'convergenceThreshold': [.05, .1],
# # 'initialSigma': [1.6, 1.2],
# #},
# {
# #'threshold': [16.0 / 3.0, 32.0 / 3.0], # 8.0 / 3.0
# 'numberOfScales': [1],
# #'maxIterations': [16, 32],
# #'convergenceThreshold': [.05, .1],
# #'initialSigma': [6.0, 3.0, 2.0, 1.6, 1.2, 1.1],
# 'initialSigma': [3.2, 1.6, 0.8],
# 'edgeEigenValueRatio': [10, 5, 3],
# },
#]
varyparams_list = [experiment_configs.featparams]
# low threshold = more keypoints
# low initialSigma = more keypoints
nKpts_list = []
cfgstr_list = []
alldictcomb = utool.flatten([utool.util_dict.all_dict_combinations(varyparams) for varyparams in featparams_list])
NUM_PASSES = 1 if not utool.get_argflag('--show') else 2
for count in range(NUM_PASSES):
for aid in qaid_list:
#for dict_ in utool.progiter(alldictcomb, lbl='feature param comb: ', total=len(alldictcomb)):
for dict_ in alldictcomb:
for key_, val_ in six.iteritems(dict_):
ibs.cfg.feat_cfg[key_] = val_
cfgstr_ = ibs.cfg.feat_cfg.get_cfgstr()
cfgstr = utool.packstr(cfgstr_, textwidth=80,
breakchars=',', newline_prefix='', break_words=False, wordsep=',')
if count == 0:
kpts = ibs.get_annot_kpts(aid)
#print('___________')
#print('len(kpts) = %r' % len(kpts))
#print(cfgstr)
nKpts_list.append(len(kpts))
cfgstr_list.append(cfgstr_)
if count == 1:
title_suffix = (' len(kpts) = %r \n' % len(kpts)) + cfgstr
viz.show_chip(ibs, aid, fnum=pt.next_fnum(),
title_suffix=title_suffix, darken=.4,
ell_linewidth=2, ell_alpha=.8)
if count == 0:
nKpts_list = np.array(nKpts_list)
cfgstr_list = np.array(cfgstr_list)
print(get_sortbystr(cfgstr_list, nKpts_list, 'cfg', 'nKpts'))
pt.present()
locals_ = locals()
return locals_
def devmain():
"""
The Developer Script
A command line interface to almost everything
-w # wait / show the gui / figures are visible
--cmd # ipython shell to play with variables
-t # run list of tests
Examples:
"""
helpstr = ut.codeblock('''
Dev is meant to be run as an interactive script.
The dev.py script runs any test you regiter with @devcmd in any combination
of configurations specified by a Config object.
Dev caches information in order to get quicker results. # FIXME: Provide quicker results # FIXME: len(line)
''')
INTRO_TITLE = 'The dev.py Script'
#INTRO_TEXT = ''.join((ut.bubbletext(INTRO_TITLE, font='cybermedium'), helpstr))
INTRO_TEXT = ut.bubbletext(INTRO_TITLE, font='cybermedium')
INTRO_STR = ut.msgblock('dev.py Intro', INTRO_TEXT)
EXAMPLE_STR = ut.msgblock('dev.py Examples', ut.codeblock(EXAMPLE_TEXT))
if ut.NOT_QUIET:
print(INTRO_STR)
if ut.get_argflag(('--help', '--verbose')):
print(EXAMPLE_STR)
CMD = ut.get_argflag('--cmd')
NOGUI = not ut.get_argflag('--gui')
if len(sys.argv) == 1:
print('Run dev.py with arguments!')
sys.exit(1)
# Run Precommands
run_devprecmds()
#
#
# Run IBEIS Main, create controller, and possibly gui
print('++dev')
main_locals = ibeis.main(gui=ut.get_argflag('--gui'))
#utool.set_process_title('IBEIS_dev')
#
#
# Load snippet variables
SNIPPITS = True and CMD
if SNIPPITS:
snippet_locals = dev_snippets(main_locals)
snippet_execstr = utool.execstr_dict(snippet_locals, 'snippet_locals')
exec(snippet_execstr)
#
#
# Development code
RUN_DEV = True # RUN_DEV = '__IPYTHON__' in vars()
if RUN_DEV:
dev_locals = run_dev(main_locals['ibs'])
dev_execstr = utool.execstr_dict(dev_locals, 'dev_locals')
exec(dev_execstr)
command = ut.get_argval('--eval', type_=str, default=None)
if command is not None:
result = eval(command, globals(), locals())
print('result = %r' % (result, ))
#ibs.search_annot_notes('360')
#
#
# Main Loop (IPython interaction, or some exec loop)
#if '--nopresent' not in sys.argv or '--noshow' in sys.argv:
ut.show_if_requested()
if ut.get_argflag(('--show', '--wshow')):
pt.present()
main_execstr = ibeis.main_loop(main_locals, ipy=(NOGUI or CMD))
exec(main_execstr)
#
#
# Memory profile
if ut.get_argflag('--memprof'):
utool.print_resource_usage()
utool.memory_profile()
print('exiting dev')
def devfunc(ibs, qaid_list):
""" Function for developing something """
print('[dev] devfunc')
import ibeis # NOQA
from ibeis.algo import Config # NOQA
#from ibeis.algo.Config import * # NOQA
feat_cfg = Config.FeatureConfig()
#feat_cfg.printme3()
print('\ncfgstr..')
print(feat_cfg.get_cfgstr())
print(utool.dict_str(feat_cfg.get_hesaff_params()))
from ibeis import viz
aid = 1
ibs.cfg.feat_cfg.threshold = 16.0 / 3.0
kpts = ibs.get_annot_kpts(aid)
print('len(kpts) = %r' % len(kpts))
from ibeis.expt import experiment_configs
#varyparams_list = [
# #{
# # 'threshold': [16.0 / 3.0, 32.0 / 3.0], # 8.0 / 3.0
# # 'numberOfScales': [3, 2, 1],
# # 'maxIterations': [16, 32],
# # 'convergenceThreshold': [.05, .1],
# # 'initialSigma': [1.6, 1.2],
# #},
# {
# #'threshold': [16.0 / 3.0, 32.0 / 3.0], # 8.0 / 3.0
# 'numberOfScales': [1],
# #'maxIterations': [16, 32],
# #'convergenceThreshold': [.05, .1],
# #'initialSigma': [6.0, 3.0, 2.0, 1.6, 1.2, 1.1],
# 'initialSigma': [3.2, 1.6, 0.8],
# 'edgeEigenValueRatio': [10, 5, 3],
# },
#]
varyparams_list = [experiment_configs.featparams]
# low threshold = more keypoints
# low initialSigma = more keypoints
nKpts_list = []
cfgstr_list = []
alldictcomb = utool.flatten([
utool.util_dict.all_dict_combinations(varyparams)
for varyparams in featparams_list
])
NUM_PASSES = 1 if not utool.get_argflag('--show') else 2
for count in range(NUM_PASSES):
for aid in qaid_list:
#for dict_ in utool.progiter(alldictcomb, lbl='feature param comb: ', total=len(alldictcomb)):
for dict_ in alldictcomb:
for key_, val_ in six.iteritems(dict_):
ibs.cfg.feat_cfg[key_] = val_
cfgstr_ = ibs.cfg.feat_cfg.get_cfgstr()
cfgstr = utool.packstr(cfgstr_,
textwidth=80,
breakchars=',',
newline_prefix='',
break_words=False,
wordsep=',')
if count == 0:
kpts = ibs.get_annot_kpts(aid)
#print('___________')
#print('len(kpts) = %r' % len(kpts))
#print(cfgstr)
nKpts_list.append(len(kpts))
cfgstr_list.append(cfgstr_)
if count == 1:
title_suffix = (' len(kpts) = %r \n' % len(kpts)) + cfgstr
viz.show_chip(ibs,
aid,
fnum=pt.next_fnum(),
title_suffix=title_suffix,
darken=.4,
ell_linewidth=2,
ell_alpha=.8)
if count == 0:
nKpts_list = np.array(nKpts_list)
cfgstr_list = np.array(cfgstr_list)
print(get_sortbystr(cfgstr_list, nKpts_list, 'cfg', 'nKpts'))
pt.present()
locals_ = locals()
return locals_
def param_interaction():
r"""
CommandLine:
python -m vtool.test_constrained_matching --test-param_interaction
Notes:
python -m vtool.test_constrained_matching --test-param_interaction
setparam normalizer_mode=nearby
setparam normalizer_mode=far
setparam ratio_thresh=.625
setparam ratio_thresh=.5
setparam ratio_thresh2=.625
normalizer_mode=plus
Example:
>>> # DISABLE_DOCTEST
>>> from vtool.test_constrained_matching import * # NOQA
>>> # build test data
>>> # execute function
>>> testtup = param_interaction()
>>> # verify results
>>> result = str(testtup)
>>> print(result)
"""
import plottool as pt
USE_IBEIS = False and ut.is_developer()
if USE_IBEIS:
from ibeis.algo.hots import devcases
index = 2
fpath1, fpath2, fpath3 = devcases.get_dev_test_fpaths(index)
testtup1 = testdata_matcher(fpath1, fpath2)
testtup2 = testdata_matcher(fpath1, fpath3)
else:
testtup1 = testdata_matcher('easy1.png', 'easy2.png')
testtup2 = testdata_matcher('easy1.png', 'hard3.png')
testtup_list = [testtup1, testtup2]
simp_list = [SimpleMatcher(testtup) for testtup in testtup_list]
varied_dict = dict([
('sver_xy_thresh', .1),
('ratio_thresh', .625),
('search_K', 7),
('ratio_thresh2', .625),
('sver_xy_thresh2', .01),
('normalizer_mode', ['nearby', 'far', 'plus'][1]),
('match_xy_thresh', .1),
])
cfgdict_list = ut.all_dict_combinations(varied_dict)
tried_configs = []
# DEFINE CUSTOM INTRACTIONS
custom_actions, valid_vizmodes, viz_index_, offset_fnum_ = make_custom_interactions(simp_list)
# /DEFINE CUSTOM INTRACTIONS
for cfgdict in ut.InteractiveIter(cfgdict_list,
#default_action='reload',
custom_actions=custom_actions,
wraparound=True):
for simp in simp_list:
simp.run_matching(cfgdict=cfgdict)
vizkey = valid_vizmodes[viz_index_[0]].replace('visualize_', '')
print('vizkey = %r' % (vizkey,))
for fnum_, simp in enumerate(simp_list):
fnum = fnum_ + offset_fnum_[0]
simp.visualize(vizkey, fnum=fnum)
tried_configs.append(cfgdict.copy())
print('Current Config = ')
print(ut.dict_str(cfgdict))
pt.present()
pt.update()
def param_interaction():
r"""
CommandLine:
python -m vtool.test_constrained_matching --test-param_interaction
Notes:
python -m vtool.test_constrained_matching --test-param_interaction
setparam normalizer_mode=nearby
setparam normalizer_mode=far
setparam ratio_thresh=.625
setparam ratio_thresh=.5
setparam ratio_thresh2=.625
normalizer_mode=plus
Example:
>>> # DISABLE_DOCTEST
>>> from vtool.test_constrained_matching import * # NOQA
>>> # build test data
>>> # execute function
>>> testtup = param_interaction()
>>> # verify results
>>> result = str(testtup)
>>> print(result)
"""
import plottool as pt
USE_IBEIS = False and ut.is_developer()
if USE_IBEIS:
from ibeis.algo.hots import devcases
index = 2
fpath1, fpath2, fpath3 = devcases.get_dev_test_fpaths(index)
testtup1 = testdata_matcher(fpath1, fpath2)
testtup2 = testdata_matcher(fpath1, fpath3)
else:
testtup1 = testdata_matcher('easy1.png', 'easy2.png')
testtup2 = testdata_matcher('easy1.png', 'hard3.png')
testtup_list = [testtup1, testtup2]
simp_list = [SimpleMatcher(testtup) for testtup in testtup_list]
varied_dict = dict([
('sver_xy_thresh', .1),
('ratio_thresh', .625),
('search_K', 7),
('ratio_thresh2', .625),
('sver_xy_thresh2', .01),
('normalizer_mode', ['nearby', 'far', 'plus'][1]),
('match_xy_thresh', .1),
])
cfgdict_list = ut.all_dict_combinations(varied_dict)
tried_configs = []
# DEFINE CUSTOM INTRACTIONS
custom_actions, valid_vizmodes, viz_index_, offset_fnum_ = make_custom_interactions(
simp_list)
# /DEFINE CUSTOM INTRACTIONS
for cfgdict in ut.InteractiveIter(
cfgdict_list,
#default_action='reload',
custom_actions=custom_actions,
wraparound=True):
for simp in simp_list:
simp.run_matching(cfgdict=cfgdict)
vizkey = valid_vizmodes[viz_index_[0]].replace('visualize_', '')
print('vizkey = %r' % (vizkey, ))
for fnum_, simp in enumerate(simp_list):
fnum = fnum_ + offset_fnum_[0]
simp.visualize(vizkey, fnum=fnum)
tried_configs.append(cfgdict.copy())
print('Current Config = ')
print(ut.dict_str(cfgdict))
pt.present()
pt.update()
# # #num_false = min(sum(is_negative), 100000)
# # gf_rank = np.nonzero(is_negative)[0][0:num_false]
# # tn_nscores.extend(sorted_nscores[gf_rank])
# # tp_nscores = np.array(tp_nscores).astype(np.float64)
# # tn_nscores = np.array(tn_nscores).astype(np.float64)
# # return tp_nscores, tn_nscores
# #tp_nscores, tn_nscores = get_labeled_name_scores(ibs, qres_list)
#from ibeis.model.hots import score_normalization
#tp_support, tn_support, tp_support_labels, tn_support_labels = score_normalization.get_ibeis_score_training_data(ibs, qaid_list, qres_list)
#ut.embed()
#x_data, y_data = results_all.get_stem_data(ibs, qaid2_qres)
#pt.plots.plot_stems(x_data, y_data)
#pt.present()
#pt.show()
#locals_ = viz_allres_annotation_scores(allres)
if __name__ == '__main__':
"""
CommandLine:
python -c "import utool, ibeis.expt.results_all; utool.doctest_funcs(ibeis.expt.results_all, allexamples=True)"
python -c "import utool, ibeis.expt.results_all; utool.doctest_funcs(ibeis.expt.results_all)"
python -m ibeis.expt.results_all --allexamples
python -m ibeis.expt.results_all --test-learn_score_normalization --enableall
"""
import multiprocessing
multiprocessing.freeze_support() # for win32
import utool as ut # NOQA
ut.doctest_funcs()
import plottool as pt # NOQA
exec(pt.present())
