def export_ibeis_to_hotspotter(ibs):
print('export to hsdb')
ibs.inject_func(get_hsdb_image_gpaths)
hsdb_dir = ibs.get_dbdir()
internal_hsdb = join(hsdb_dir, '_hsdb')
utool.ensuredir(internal_hsdb)
# Build Image Table
gid_list = ibs.get_valid_gids()
gpath_list = ibs.get_hsdb_image_gpaths(gid_list)
reviewed_list = ibs.get_image_reviewed(gid_list)
# aif in hotspotter is equivilant to reviewed in IBEIS
image_table_csv = utool.make_csv_table(
[gid_list, gpath_list, reviewed_list],
['gid', 'gname', 'aif'],
'# image table')
# Build Name Table
nid_list = ibs.get_valid_nids()
name_list = ibs.get_name_text(nid_list)
name_table_csv = utool.make_csv_table(
[nid_list, name_list],
['nid', 'name'],
'# name table')
# Build Chip Table
aid_list = ibs.get_valid_aids()
annotationgid_list = ibs.get_annot_gids(aid_list)
annotationnid_list = ibs.get_annot_nids(aid_list)
bbox_list = map(list, ibs.get_annot_bboxes(aid_list))
theta_list = ibs.get_annot_thetas(aid_list)
notes_list = ibs.get_annot_notes(aid_list)
chip_column_list = [aid_list, annotationgid_list, annotationnid_list, bbox_list, theta_list, notes_list]
chip_column_lbls = ['cid', 'gid', 'nid', '[tlx tly w h]', 'theta', 'notes']
chip_column_types = [int, int, int, list, float, str]
chip_table_csv = utool.make_csv_table(
chip_column_list,
chip_column_lbls,
'# chip table', chip_column_types)
if utool.VERBOSE:
if len(aid_list) < 87:
print(chip_table_csv)
if len(nid_list) < 87:
print(name_table_csv)
if len(gid_list) < 87:
print(image_table_csv)
# Write Tables
with open(join(internal_hsdb, 'HSDB_image_table.csv'), 'wb') as imgtbl_file:
imgtbl_file.write(image_table_csv)
with open(join(internal_hsdb, 'HSDB_name_table.csv'), 'wb') as nametbl_file:
nametbl_file.write(name_table_csv)
with open(join(internal_hsdb, 'HSDB_chip_table.csv'), 'wb') as chiptbl_file:
chiptbl_file.write(chip_table_csv)
def get_flat_table(ibs):
""" Dumps hotspotter flat tables """
aid_list = ibs.get_valid_aids()
column_tups = [
(int, 'aids', aid_list,),
(str, 'names', ibs.get_annot_names(aid_list),),
(list, 'bbox', map(list, ibs.get_annot_bboxes(aid_list),)),
(float, 'theta', ibs.get_annot_thetas(aid_list),),
(str, 'gpaths', ibs.get_annot_gpaths(aid_list),),
(str, 'notes', ibs.get_annot_notes(aid_list),),
(str, 'uuids', ibs.get_annot_uuids(aid_list),),
]
column_type = [tup[0] for tup in column_tups]
column_lbls = [tup[1] for tup in column_tups]
column_list = [tup[2] for tup in column_tups]
header = '\n'.join([
'# Roi Flat Table',
'# aid - internal annotation index (not gaurenteed unique)',
'# name - animal identity',
'# bbox - bounding box [tlx tly w h] in image',
'# theta - bounding box orientation',
'# gpath - image filepath',
'# notes - user defined notes',
'# uuids - unique universal ids (gaurenteed unique)',
])
flat_table_str = utool.make_csv_table(column_list, column_lbls, header,
column_type)
return flat_table_str
def print_next_rankmat():
# Prints nextbest ranks
print('-------------')
print('NextRankMat: %s' % testnameid)
header = (' top false rank matrix: rows=queries, cols=cfgs:')
print('\n'.join(cfgx2_lbl))
column_list = cfgx2_nextbestranks
print(ut.make_csv_table(column_list, row_lbls=testres.qaids,
column_lbls=column_lbls, header=header,
transpose=False,
use_lbl_width=len(cfgx2_lbl) < 5))
def print_next_rankmat():
# Prints nextbest ranks
print('-------------')
print('NextRankMat: %s' % testnameid)
header = (' top false rank matrix: rows=queries, cols=cfgs:')
print('\n'.join(cfgx2_lbl))
column_list = cfgx2_nextbestranks
print(
ut.make_csv_table(column_list,
row_lbls=testres.qaids,
column_lbls=column_lbls,
header=header,
transpose=False,
use_lbl_width=len(cfgx2_lbl) < 5))
def print_scorediff_mat():
# Prints nextbest ranks
print('-------------')
print('ScoreDiffMat: %s' % testnameid)
header = (' score difference between top true and top false: rows=queries, cols=cfgs:')
print('\n'.join(cfgx2_lbl))
column_list = cfgx2_scorediffs
column_type = [float] * len(column_list)
print(ut.make_csv_table(column_list, row_lbls=testres.qaids,
column_lbls=column_lbls,
column_type=column_type,
header=header,
transpose=False,
use_lbl_width=len(cfgx2_lbl) < 5))
def get_hots_flat_table(ibs):
""" Dumps hotspotter flat tables
Args:
ibs (IBEISController): ibeis controller object
Returns:
str: flat_table_str
CommandLine:
python -m ibeis.dbio.export_hsdb --exec-get_hots_flat_table
Example:
>>> # ENABLE_DOCTEST
>>> from ibeis.dbio.export_hsdb import * # NOQA
>>> import ibeis
>>> ibs = ibeis.opendb(defaultdb='testdb1')
>>> flat_table_str = get_hots_flat_table(ibs)
>>> result = ('flat_table_str = %s' % (str(flat_table_str),))
>>> print(result)
"""
aid_list = ibs.get_valid_aids()
column_tups = [
(int, "aids", aid_list),
(str, "names", ibs.get_annot_names(aid_list)),
(list, "bbox", list(map(list, ibs.get_annot_bboxes(aid_list)))),
(float, "theta", ibs.get_annot_thetas(aid_list)),
(str, "gpaths", ibs.get_annot_image_paths(aid_list)),
(str, "notes", ibs.get_annot_notes(aid_list)),
(str, "uuids", ibs.get_annot_uuids(aid_list)),
]
column_type = [tup[0] for tup in column_tups]
column_lbls = [tup[1] for tup in column_tups]
column_list = [tup[2] for tup in column_tups]
header = "\n".join(
[
"# Roi Flat Table",
"# aid - internal annotation index (not gaurenteed unique)",
"# name - animal identity",
"# bbox - bounding box [tlx tly w h] in image",
"# theta - bounding box orientation",
"# gpath - image filepath",
"# notes - user defined notes",
"# uuids - unique universal ids (gaurenteed unique)",
]
)
flat_table_str = ut.make_csv_table(column_list, column_lbls, header, column_type)
return flat_table_str
def get_table_csv(db, tablename, exclude_columns=[]):
""" Conveinience: Converts a tablename to csv format """
column_nametypes = db.table_columns[tablename]
column_names = [name for (name, type_) in column_nametypes]
column_list = []
column_lbls = []
for name in column_names:
if name in exclude_columns:
continue
column_vals = db.get_column(tablename, name)
column_list.append(column_vals)
column_lbls.append(name.replace(tablename[:-1] + '_', ''))
# remove column prefix for more compact csvs
#=None, column_list=[], header='', column_type=None
header = db.get_table_csv_header(tablename)
csv_table = utool.make_csv_table(column_list, column_lbls, header)
return csv_table
def test_language_modulus():
"""
References:
http://en.wikipedia.org/wiki/Modulo_operation
"""
import math
import utool as ut
TAU = math.pi * 2
num_list = [-8, -1, 0, 1, 2, 6, 7, 29]
modop_result_list = []
fmod_result_list = []
for num in num_list:
num = float(num)
modop_result_list.append(num % TAU)
fmod_result_list.append(math.fmod(num, TAU))
table = ut.make_csv_table([num_list, modop_result_list, fmod_result_list],
['num', 'modop', 'fmod'], 'mods', [float, float, float] )
print(table)
def print_scorediff_mat():
# Prints nextbest ranks
print('-------------')
print('ScoreDiffMat: %s' % testnameid)
header = (
' score difference between top true and top false: rows=queries, cols=cfgs:'
)
print('\n'.join(cfgx2_lbl))
column_list = cfgx2_scorediffs
column_type = [float] * len(column_list)
print(
ut.make_csv_table(column_list,
row_lbls=testres.qaids,
column_lbls=column_lbls,
column_type=column_type,
header=header,
transpose=False,
use_lbl_width=len(cfgx2_lbl) < 5))
def test_language_modulus():
"""
References:
http://en.wikipedia.org/wiki/Modulo_operation
"""
import math
import utool as ut
TAU = math.pi * 2
num_list = [-8, -1, 0, 1, 2, 6, 7, 29]
modop_result_list = []
fmod_result_list = []
for num in num_list:
num = float(num)
modop_result_list.append(num % TAU)
fmod_result_list.append(math.fmod(num, TAU))
table = ut.make_csv_table([num_list, modop_result_list, fmod_result_list],
['num', 'modop', 'fmod'], 'mods',
[float, float, float])
print(table)
def get_table_csv(cur, tablename, exclude_columns=[]):
""" Conveinience: Converts a tablename to csv format
Args:
tablename (str):
exclude_columns (list):
Returns:
str: csv_table
CommandLine:
python -m ibeis.control.SQLDatabaseControl --test-get_table_csv
Example:
>>> # ENABLE_DOCTEST
>>> from ibeis.control.SQLDatabaseControl import * # NOQA
>>> # build test data
>>> import ibeis
>>> ibs = ibeis.opendb('testdb1')
>>> db = ibs.db
>>> tablename = ibeis.const.NAME_TABLE
>>> exclude_columns = []
>>> # execute function
>>> csv_table = db.get_table_csv(tablename, exclude_columns)
>>> # verify results
>>> result = str(csv_table)
>>> print(result)
"""
import utool as ut
colnames_ = ut.get_table_columnname_list(cur, tablename)
colnames = tuple([colname for colname in colnames_ if colname not in exclude_columns])
row_list = ut.get_table_rows(cur, tablename, colnames, unpack=False)
column_list = zip(*row_list)
#=None, column_list=[], header='', column_type=None
#import utool as ut
#column_list, column_names = db.get_table_column_data(tablename, exclude_columns)
# remove column prefix for more compact csvs
column_lbls = [name.replace(tablename[:-1] + '_', '') for name in colnames]
#header = db.get_table_csv_header(tablename)
header = ''
csv_table = ut.make_csv_table(column_list, column_lbls, header)
return csv_table
def get_table_csv(cur, tablename, exclude_columns=[]):
""" Conveinience: Converts a tablename to csv format
Args:
tablename (str):
exclude_columns (list):
Returns:
str: csv_table
CommandLine:
python -m ibeis.control.SQLDatabaseControl --test-get_table_csv
Example:
>>> # ENABLE_DOCTEST
>>> from ibeis.control.SQLDatabaseControl import * # NOQA
>>> # build test data
>>> import ibeis
>>> ibs = ibeis.opendb('testdb1')
>>> db = ibs.db
>>> tablename = ibeis.const.NAME_TABLE
>>> exclude_columns = []
>>> # execute function
>>> csv_table = db.get_table_csv(tablename, exclude_columns)
>>> # verify results
>>> result = str(csv_table)
>>> print(result)
"""
import utool as ut
colnames_ = ut.get_table_columnname_list(cur, tablename)
colnames = tuple([colname for colname in colnames_ if colname not in exclude_columns])
row_list = ut.get_table_rows(cur, tablename, colnames, unpack=False)
column_list = zip(*row_list)
#=None, column_list=[], header='', column_type=None
#import utool as ut
#column_list, column_names = db.get_table_column_data(tablename, exclude_columns)
# remove column prefix for more compact csvs
column_lbls = [name.replace(tablename[:-1] + '_', '') for name in colnames]
#header = db.get_table_csv_header(tablename)
header = ''
csv_table = ut.make_csv_table(column_list, column_lbls, header)
return csv_table
def nice_table(self):
import utool as ut
return ut.make_csv_table(ut.listT(self.row_data), raw=True)
def get_hots_table_strings(ibs):
r"""
Args:
ibs (IBEISController): wbia controller object
CommandLine:
python -m wbia.dbio.export_hsdb --test-get_hots_table_strings
Example:
>>> # ENABLE_DOCTEST
>>> from wbia.dbio.export_hsdb import * # NOQA
>>> import wbia
>>> # build test data
>>> ibs = wbia.opendb('testdb1')
>>> ibs.delete_empty_nids()
>>> # execute function
>>> csvtup = get_hots_table_strings(ibs)
>>> # hack so hashtag is at the end of each line
>>> result = '\n'.join(csvtup).replace('\n', '#\n') + '#'
>>> # verify results
>>> print(result)
# image table#
# num_rows=13#
# gid, gname, aif#
1, ../_ibsdb/images/66ec193a-1619-b3b6-216d-1784b4833b61.jpg, 0#
2, ../_ibsdb/images/d8903434-942f-e0f5-d6c2-0dcbe3137bf7.jpg, 0#
3, ../_ibsdb/images/b73b72f4-4acb-c445-e72c-05ce02719d3d.jpg, 0#
4, ../_ibsdb/images/0cd05978-3d83-b2ee-2ac9-798dd571c3b3.jpg, 0#
5, ../_ibsdb/images/0a9bc03d-a75e-8d14-0153-e2949502aba7.jpg, 0#
6, ../_ibsdb/images/2deeff06-5546-c752-15dc-2bd0fdb1198a.jpg, 0#
7, ../_ibsdb/images/a9b70278-a936-c1dd-8a3b-bc1e9a998bf0.png, 0#
8, ../_ibsdb/images/42fdad98-369a-2cbc-67b1-983d6d6a3a60.jpg, 0#
9, ../_ibsdb/images/c459d381-fd74-1d99-6215-e42e3f432ea9.jpg, 0#
10, ../_ibsdb/images/33fd9813-3a2b-774b-3fcc-4360d1ae151b.jpg, 0#
11, ../_ibsdb/images/97e8ea74-873f-2092-b372-f928a7be30fa.jpg, 0#
12, ../_ibsdb/images/588bc218-83a5-d400-21aa-d499832632b0.jpg, 0#
13, ../_ibsdb/images/163a890c-36f2-981e-3529-c552b6d668a3.jpg, 0#
# name table#
# num_rows=7#
# nid, name#
1, easy#
2, hard#
3, jeff#
4, lena#
5, occl#
6, polar#
7, zebra#
# chip table#
# num_rows=13#
# cid, gid, nid, [tlx tly w h], theta, notes#
1, 1, -1, [0 0 1047 715], 0.00, aid 1 and 2 are correct matches#
2, 2, 1, [0 0 1035 576], 0.00, #
3, 3, 1, [0 0 1072 804], 0.00, #
4, 4, -4, [0 0 1072 804], 0.00, #
5, 5, 2, [0 0 1072 804], 0.00, #
6, 6, 2, [0 0 450 301], 0.00, #
7, 7, 3, [0 0 400 400], 0.00, very simple image to debug feature detector#
8, 8, 4, [0 0 220 220], 0.00, standard test image#
9, 9, -9, [0 0 450 284], 0.00, this is actually a plains zebra#
10, 10, 5, [0 0 450 341], 0.00, this is actually a plains zebra#
11, 11, -11, [0 0 741 734], 0.00, #
12, 12, 6, [0 0 673 634], 0.00, #
13, 13, 7, [0 0 1114 545], 0.00, #
"""
logger.info('export to hsdb')
# ibs.inject_func(get_hsdb_image_gpaths)
# Build Image Table
gid_list = ibs.get_valid_gids()
gpath_list = get_hsdb_image_gpaths(ibs, gid_list)
reviewed_list = ibs.get_image_reviewed(gid_list)
# aif in hotspotter is equivilant to reviewed in IBEIS
image_table_csv = ut.make_csv_table([gid_list, gpath_list, reviewed_list],
['gid', 'gname', 'aif'],
'# image table')
# Build Name Table
nid_list = ibs.get_valid_nids()
name_list = ibs.get_name_texts(nid_list)
name_table_csv = ut.make_csv_table([nid_list, name_list], ['nid', 'name'],
'# name table')
# Build Chip Table
aid_list = ibs.get_valid_aids()
annotationgid_list = ibs.get_annot_gids(aid_list)
annotationnid_list = ibs.get_annot_name_rowids(aid_list)
bbox_list = list(map(list, ibs.get_annot_bboxes(aid_list)))
theta_list = ibs.get_annot_thetas(aid_list)
notes_list = ibs.get_annot_notes(aid_list)
chip_column_list = [
aid_list,
annotationgid_list,
annotationnid_list,
bbox_list,
theta_list,
notes_list,
]
chip_column_lbls = ['cid', 'gid', 'nid', '[tlx tly w h]', 'theta', 'notes']
chip_column_types = [int, int, int, list, float, str]
chip_table_csv = ut.make_csv_table(chip_column_list, chip_column_lbls,
'# chip table', chip_column_types)
if ut.VERBOSE:
if len(aid_list) < 87:
logger.info(chip_table_csv)
if len(nid_list) < 87:
logger.info(name_table_csv)
if len(gid_list) < 87:
logger.info(image_table_csv)
return image_table_csv, name_table_csv, chip_table_csv
def get_hots_flat_table(ibs):
""" Dumps hotspotter flat tables
Args:
ibs (IBEISController): wbia controller object
Returns:
str: flat_table_str
CommandLine:
python -m wbia.dbio.export_hsdb --exec-get_hots_flat_table
Example:
>>> # ENABLE_DOCTEST
>>> from wbia.dbio.export_hsdb import * # NOQA
>>> import wbia
>>> ibs = wbia.opendb(defaultdb='testdb1')
>>> flat_table_str = get_hots_flat_table(ibs)
>>> result = ('flat_table_str = %s' % (str(flat_table_str),))
>>> print(result)
"""
aid_list = ibs.get_valid_aids()
column_tups = [
(
int,
'aids',
aid_list,
),
(
str,
'names',
ibs.get_annot_names(aid_list),
),
(list, 'bbox', list(map(
list,
ibs.get_annot_bboxes(aid_list),
))),
(
float,
'theta',
ibs.get_annot_thetas(aid_list),
),
(
str,
'gpaths',
ibs.get_annot_image_paths(aid_list),
),
(
str,
'notes',
ibs.get_annot_notes(aid_list),
),
(
str,
'uuids',
ibs.get_annot_uuids(aid_list),
),
]
column_type = [tup[0] for tup in column_tups]
column_lbls = [tup[1] for tup in column_tups]
column_list = [tup[2] for tup in column_tups]
header = '\n'.join([
'# Roi Flat Table',
'# aid - internal annotation index (not gaurenteed unique)',
'# name - animal identity',
'# bbox - bounding box [tlx tly w h] in image',
'# theta - bounding box orientation',
'# gpath - image filepath',
'# notes - user defined notes',
'# uuids - unique universal ids (gaurenteed unique)',
])
flat_table_str = ut.make_csv_table(column_list, column_lbls, header,
column_type)
return flat_table_str
def printme3(self):
column_list = [self.qaids, self.aids, self.scores, self.ranks]
column_lbls = ['qaids', 'aids', 'scores', 'ranks']
header = 'Orgres %s' % (self.orgtype)
print(utool.make_csv_table(column_list, column_lbls, header, column_type=None))
def get_hots_table_strings(ibs):
r"""
Args:
ibs (IBEISController): ibeis controller object
CommandLine:
python -m ibeis.dbio.export_hsdb --test-get_hots_table_strings
Example:
>>> # ENABLE_DOCTEST
>>> from ibeis.dbio.export_hsdb import * # NOQA
>>> import ibeis
>>> # build test data
>>> ibs = ibeis.opendb('testdb1')
>>> ibs.delete_empty_nids()
>>> # execute function
>>> csvtup = get_hots_table_strings(ibs)
>>> # hack so hashtag is at the end of each line
>>> result = '\n'.join(csvtup).replace('\n', '#\n') + '#'
>>> # verify results
>>> print(result)
# image table#
# num_rows=13#
# gid, gname, aif#
1, ../_ibsdb/images/66ec193a-1619-b3b6-216d-1784b4833b61.jpg, 0#
2, ../_ibsdb/images/d8903434-942f-e0f5-d6c2-0dcbe3137bf7.jpg, 0#
3, ../_ibsdb/images/b73b72f4-4acb-c445-e72c-05ce02719d3d.jpg, 0#
4, ../_ibsdb/images/0cd05978-3d83-b2ee-2ac9-798dd571c3b3.jpg, 0#
5, ../_ibsdb/images/0a9bc03d-a75e-8d14-0153-e2949502aba7.jpg, 0#
6, ../_ibsdb/images/2deeff06-5546-c752-15dc-2bd0fdb1198a.jpg, 0#
7, ../_ibsdb/images/a9b70278-a936-c1dd-8a3b-bc1e9a998bf0.png, 0#
8, ../_ibsdb/images/42fdad98-369a-2cbc-67b1-983d6d6a3a60.jpg, 0#
9, ../_ibsdb/images/c459d381-fd74-1d99-6215-e42e3f432ea9.jpg, 0#
10, ../_ibsdb/images/33fd9813-3a2b-774b-3fcc-4360d1ae151b.jpg, 0#
11, ../_ibsdb/images/97e8ea74-873f-2092-b372-f928a7be30fa.jpg, 0#
12, ../_ibsdb/images/588bc218-83a5-d400-21aa-d499832632b0.jpg, 0#
13, ../_ibsdb/images/163a890c-36f2-981e-3529-c552b6d668a3.jpg, 0#
# name table#
# num_rows=7#
# nid, name#
1, easy#
2, hard#
3, jeff#
4, lena#
5, occl#
6, polar#
7, zebra#
# chip table#
# num_rows=13#
# cid, gid, nid, [tlx tly w h], theta, notes#
1, 1, -1, [0 0 1047 715], 0.00, aid 1 and 2 are correct matches#
2, 2, 1, [0 0 1035 576], 0.00, #
3, 3, 1, [0 0 1072 804], 0.00, #
4, 4, -4, [0 0 1072 804], 0.00, #
5, 5, 2, [0 0 1072 804], 0.00, #
6, 6, 2, [0 0 450 301], 0.00, #
7, 7, 3, [0 0 400 400], 0.00, very simple image to debug feature detector#
8, 8, 4, [0 0 220 220], 0.00, standard test image#
9, 9, -9, [0 0 450 284], 0.00, this is actually a plains zebra#
10, 10, 5, [0 0 450 341], 0.00, this is actually a plains zebra#
11, 11, -11, [0 0 741 734], 0.00, #
12, 12, 6, [0 0 673 634], 0.00, #
13, 13, 7, [0 0 1114 545], 0.00, #
"""
print("export to hsdb")
# ibs.inject_func(get_hsdb_image_gpaths)
# Build Image Table
gid_list = ibs.get_valid_gids()
gpath_list = get_hsdb_image_gpaths(ibs, gid_list)
reviewed_list = ibs.get_image_reviewed(gid_list)
# aif in hotspotter is equivilant to reviewed in IBEIS
image_table_csv = ut.make_csv_table([gid_list, gpath_list, reviewed_list], ["gid", "gname", "aif"], "# image table")
# Build Name Table
nid_list = ibs.get_valid_nids()
name_list = ibs.get_name_texts(nid_list)
name_table_csv = ut.make_csv_table([nid_list, name_list], ["nid", "name"], "# name table")
# Build Chip Table
aid_list = ibs.get_valid_aids()
annotationgid_list = ibs.get_annot_gids(aid_list)
annotationnid_list = ibs.get_annot_name_rowids(aid_list)
bbox_list = list(map(list, ibs.get_annot_bboxes(aid_list)))
theta_list = ibs.get_annot_thetas(aid_list)
notes_list = ibs.get_annot_notes(aid_list)
chip_column_list = [aid_list, annotationgid_list, annotationnid_list, bbox_list, theta_list, notes_list]
chip_column_lbls = ["cid", "gid", "nid", "[tlx tly w h]", "theta", "notes"]
chip_column_types = [int, int, int, list, float, str]
chip_table_csv = ut.make_csv_table(chip_column_list, chip_column_lbls, "# chip table", chip_column_types)
if ut.VERBOSE:
if len(aid_list) < 87:
print(chip_table_csv)
if len(nid_list) < 87:
print(name_table_csv)
if len(gid_list) < 87:
print(image_table_csv)
return image_table_csv, name_table_csv, chip_table_csv
def nice_table(self):
import utool as ut
return ut.make_csv_table(ut.listT(self.row_data), raw=True)
