def gridsearch_coverage_grid_mask():
"""
CommandLine:
python -m vtool.coverage_grid --test-gridsearch_coverage_grid_mask --show
Example:
>>> # DISABLE_DOCTEST
>>> from vtool.coverage_grid import * # NOQA
>>> import plottool as pt
>>> gridsearch_coverage_grid_mask()
>>> pt.show_if_requested()
"""
import plottool as pt
cfgdict_list, cfglbl_list = get_coverage_grid_gridsearch_configs()
kpts, chipsize, weights = coverage_kpts.testdata_coverage('easy1.png')
gridmask_list = [
255 * make_grid_coverage_mask(kpts, chipsize, weights, **cfgdict)
for cfgdict in ut.ProgressIter(cfgdict_list, lbl='coverage grid')
]
NORMHACK = False
if NORMHACK:
gridmask_list = [
255 * (gridmask / gridmask.max()) for gridmask in gridmask_list
]
fnum = 1
ut.interact_gridsearch_result_images(
pt.imshow, cfgdict_list, cfglbl_list,
gridmask_list, fnum=fnum, figtitle='coverage grid', unpack=False,
max_plots=25)
pt.iup()
def gridsearch_kpts_coverage_mask():
"""
testing function
CommandLine:
python -m vtool.coverage_kpts --test-gridsearch_kpts_coverage_mask --show
Example:
>>> # DISABLE_DOCTEST
>>> from vtool.coverage_kpts import * # NOQA
>>> import plottool as pt
>>> gridsearch_kpts_coverage_mask()
>>> pt.show_if_requested()
"""
import plottool as pt
cfgdict_list, cfglbl_list = get_coverage_kpts_gridsearch_configs()
kpts, chipsize, weights = testdata_coverage('easy1.png')
imgmask_list = [
255 * make_kpts_coverage_mask(kpts, chipsize, weights,
return_patch=False, **cfgdict)
for cfgdict in ut.ProgressIter(cfgdict_list, lbl='coverage grid')
]
#NORMHACK = True
#if NORMHACK:
# imgmask_list = [
# 255 * (mask / mask.max()) for mask in imgmask_list
# ]
fnum = pt.next_fnum()
ut.interact_gridsearch_result_images(
pt.imshow, cfgdict_list, cfglbl_list,
imgmask_list, fnum=fnum, figtitle='coverage image', unpack=False,
max_plots=25)
pt.iup()
def gridsearch_coverage_grid():
"""
CommandLine:
python -m vtool.coverage_grid --test-gridsearch_coverage_grid --show
Example:
>>> # DISABLE_DOCTEST
>>> from vtool.coverage_grid import * # NOQA
>>> import plottool as pt
>>> gridsearch_coverage_grid()
>>> pt.show_if_requested()
"""
import plottool as pt
fname = None # 'easy1.png'
kpts, chipsize, weights = coverage_kpts.testdata_coverage(fname)
if len(kpts) > 100:
kpts = kpts[::100]
weights = weights[::100]
cfgdict_list, cfglbl_list = get_coverage_grid_gridsearch_configs()
coverage_gridtup_list = [
sparse_grid_coverage(kpts, chipsize, weights, **cfgdict)
for cfgdict in ut.ProgressIter(cfgdict_list, lbl='coverage grid')
]
fnum = 1
with ut.Timer('plotting gridsearch'):
ut.interact_gridsearch_result_images(
show_coverage_grid, cfgdict_list, cfglbl_list,
coverage_gridtup_list, fnum=fnum, figtitle='coverage grid', unpack=True,
max_plots=25)
pt.iup()
def gridsearch_image_function(param_info,
test_func,
args=tuple(),
show_func=None):
"""
gridsearch for a function that produces a single image
"""
import plottool as pt
cfgdict_list, cfglbl_list = param_info.get_gridsearch_input(
defaultslice=slice(0, 10))
fnum = pt.ensure_fnum(None)
if show_func is None:
show_func = pt.imshow
lbl = ut.get_funcname(test_func)
cfgresult_list = [
test_func(*args, **cfgdict)
for cfgdict in ut.ProgressIter(cfgdict_list, lbl=lbl)
]
onclick_func = None
ut.interact_gridsearch_result_images(show_func,
cfgdict_list,
cfglbl_list,
cfgresult_list,
fnum=fnum,
figtitle=lbl,
unpack=False,
max_plots=25,
onclick_func=onclick_func)
pt.iup()
def gridsearch_image_function(param_info, test_func, args=tuple(), show_func=None):
"""
gridsearch for a function that produces a single image
"""
import plottool as pt
cfgdict_list, cfglbl_list = param_info.get_gridsearch_input(defaultslice=slice(0, 10))
fnum = pt.ensure_fnum(None)
if show_func is None:
show_func = pt.imshow
lbl = ut.get_funcname(test_func)
cfgresult_list = [
test_func(*args, **cfgdict)
for cfgdict in ut.ProgressIter(cfgdict_list, lbl=lbl)
]
onclick_func = None
ut.interact_gridsearch_result_images(
show_func, cfgdict_list, cfglbl_list,
cfgresult_list, fnum=fnum,
figtitle=lbl, unpack=False,
max_plots=25, onclick_func=onclick_func)
pt.iup()
def gridsearch_kpts_coverage_mask():
"""
testing function
CommandLine:
python -m vtool.coverage_kpts --test-gridsearch_kpts_coverage_mask --show
Example:
>>> # DISABLE_DOCTEST
>>> from vtool.coverage_kpts import * # NOQA
>>> import plottool as pt
>>> gridsearch_kpts_coverage_mask()
>>> pt.show_if_requested()
"""
import plottool as pt
cfgdict_list, cfglbl_list = get_coverage_kpts_gridsearch_configs()
kpts, chipsize, weights = testdata_coverage('easy1.png')
imgmask_list = [
255 * make_kpts_coverage_mask(
kpts, chipsize, weights, return_patch=False, **cfgdict)
for cfgdict in ut.ProgressIter(cfgdict_list, lbl='coverage grid')
]
#NORMHACK = True
#if NORMHACK:
# imgmask_list = [
# 255 * (mask / mask.max()) for mask in imgmask_list
# ]
fnum = pt.next_fnum()
ut.interact_gridsearch_result_images(pt.imshow,
cfgdict_list,
cfglbl_list,
imgmask_list,
fnum=fnum,
figtitle='coverage image',
unpack=False,
max_plots=25)
pt.iup()
def gridsearch_chipextract():
r"""
CommandLine:
python -m vtool.chip --test-gridsearch_chipextract --show
Example:
>>> # GRIDSEARCH
>>> from vtool.chip import * # NOQA
>>> gridsearch_chipextract()
>>> ut.show_if_requested()
"""
import cv2
test_func = extract_chip_from_img
if False:
gpath = ut.grab_test_imgpath('carl.jpg')
bbox = (100, 3, 100, 100)
theta = 0.0
new_size = (58, 34)
else:
gpath = '/media/raid/work/GZ_Master1/_ibsdb/images/1524525d-2131-8770-d27c-3a5f9922e9e9.jpg'
bbox = (450, 373, 2062, 1124)
theta = 0.0
old_size = bbox[2:4]
#target_area = 700 ** 2
target_area = 1200 ** 2
new_size = get_scaled_sizes_with_area(target_area, [old_size])[0]
print('old_size = %r' % (old_size,))
print('new_size = %r' % (new_size,))
#new_size = (677, 369)
imgBGR = gtool.imread(gpath)
args = (imgBGR, bbox, theta, new_size)
param_info = ut.ParamInfoList('extract_params', [
ut.ParamInfo('interpolation', cv2.INTER_LANCZOS4,
varyvals=[
cv2.INTER_LANCZOS4,
cv2.INTER_CUBIC,
cv2.INTER_LINEAR,
cv2.INTER_NEAREST,
#cv2.INTER_AREA
],)
])
show_func = None
# Generalize
import plottool as pt
pt.imshow(imgBGR) # HACK
cfgdict_list, cfglbl_list = param_info.get_gridsearch_input(defaultslice=slice(0, 10))
fnum = pt.ensure_fnum(None)
if show_func is None:
show_func = pt.imshow
lbl = ut.get_funcname(test_func)
cfgresult_list = [
test_func(*args, **cfgdict)
for cfgdict in ut.ProgressIter(cfgdict_list, lbl=lbl)
]
onclick_func = None
ut.interact_gridsearch_result_images(
show_func, cfgdict_list, cfglbl_list,
cfgresult_list, fnum=fnum,
figtitle=lbl, unpack=False,
max_plots=25, onclick_func=onclick_func)
pt.iup()
def tst_single_annot_distinctiveness_params(ibs, aid):
r"""
CommandLine:
python -m wbia.algo.hots.distinctiveness_normalizer --test-test_single_annot_distinctiveness_params --show
python -m wbia.algo.hots.distinctiveness_normalizer --test-test_single_annot_distinctiveness_params --show --db GZ_ALL
Example:
>>> # DISABLE_DOCTEST
>>> from wbia.algo.hots.distinctiveness_normalizer import * # NOQA
>>> import wbia.plottool as pt
>>> import wbia
>>> # build test data
>>> ibs = wbia.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 wbia.init.main_commands import postload_commands
from wbia.algo import Config
postload_commands(ibs, None)
import wbia.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()
logger.info('Varied Dict: ')
logger.info(ut.repr2(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 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 gridsearch_chipextract():
r"""
CommandLine:
python -m vtool.chip --test-gridsearch_chipextract --show
Example:
>>> # GRIDSEARCH
>>> from vtool.chip import * # NOQA
>>> gridsearch_chipextract()
>>> ut.show_if_requested()
"""
import cv2
test_func = extract_chip_from_img
if False:
gpath = ut.grab_test_imgpath('carl.jpg')
bbox = (100, 3, 100, 100)
theta = 0.0
new_size = (58, 34)
else:
gpath = '/media/raid/work/GZ_Master1/_ibsdb/images/1524525d-2131-8770-d27c-3a5f9922e9e9.jpg'
bbox = (450, 373, 2062, 1124)
theta = 0.0
old_size = bbox[2:4]
#target_area = 700 ** 2
target_area = 1200**2
new_size = get_scaled_sizes_with_area(target_area, [old_size])[0]
print('old_size = %r' % (old_size, ))
print('new_size = %r' % (new_size, ))
#new_size = (677, 369)
imgBGR = gtool.imread(gpath)
args = (imgBGR, bbox, theta, new_size)
param_info = ut.ParamInfoList(
'extract_params',
[
ut.ParamInfo(
'interpolation',
cv2.INTER_LANCZOS4,
varyvals=[
cv2.INTER_LANCZOS4,
cv2.INTER_CUBIC,
cv2.INTER_LINEAR,
cv2.INTER_NEAREST,
#cv2.INTER_AREA
],
)
])
show_func = None
# Generalize
import plottool as pt
pt.imshow(imgBGR) # HACK
cfgdict_list, cfglbl_list = param_info.get_gridsearch_input(
defaultslice=slice(0, 10))
fnum = pt.ensure_fnum(None)
if show_func is None:
show_func = pt.imshow
lbl = ut.get_funcname(test_func)
cfgresult_list = [
test_func(*args, **cfgdict)
for cfgdict in ut.ProgressIter(cfgdict_list, lbl=lbl)
]
onclick_func = None
ut.interact_gridsearch_result_images(show_func,
cfgdict_list,
cfglbl_list,
cfgresult_list,
fnum=fnum,
figtitle=lbl,
unpack=False,
max_plots=25,
onclick_func=onclick_func)
pt.iup()
