def get_annotmatch_rowid_from_undirected_superkey(ibs, aids1, aids2):
# The directed nature of this makes a few things difficult and may cause
# odd behavior
am_rowids = ibs.get_annotmatch_rowid_from_superkey(aids1, aids2)
idxs = ut.where([r is None for r in am_rowids])
# Check which ones are None
aids1_ = ut.take(aids1, idxs)
aids2_ = ut.take(aids2, idxs)
am_rowids_ = ibs.get_annotmatch_rowid_from_superkey(aids2_, aids1_)
# Use the other rowid if found
for idx, rowid in zip(idxs, am_rowids_):
am_rowids[idx] = rowid
return am_rowids
def expand_input(inputs, index, inplace=False):
"""
Pushes the rootmost inputs all the way up to the sources of the graph
CommandLine:
python -m dtool.input_helpers expand_input
Example:
>>> # ENABLE_DOCTEST
>>> from dtool.input_helpers import * # NOQA
>>> from dtool.example_depcache2 import * # NOQA
>>> depc = testdata_depc4()
>>> inputs = depc['smk_match'].rootmost_inputs
>>> inputs = depc['neighbs'].rootmost_inputs
>>> print('(pre-expand) inputs = %r' % (inputs,))
>>> index = 'indexer'
>>> inputs2 = inputs.expand_input(index)
>>> print('(post-expand) inputs2 = %r' % (inputs2,))
>>> assert 'indexer' in str(inputs), 'missing indexer1'
>>> assert 'indexer' not in str(inputs2), (
>>> '(2) unexpected indexer in %s' % (inputs2,))
"""
if isinstance(index, six.string_types):
index_list = ut.where(
[rmi.tablename == index for rmi in inputs.rmi_list])
if len(index_list) == 0:
index = 0
else:
index = index_list[0]
rmi = inputs.rmi_list[index]
parent_level = rmi.parent_level()
if len(parent_level) == 0:
#raise AssertionError('no parents to expand')
new_rmi_list = inputs.rmi_list[:]
else:
new_rmi_list = ut.insert_values(inputs.rmi_list, index,
parent_level, inplace)
new_rmi_list = ut.unique(new_rmi_list)
if inplace:
inputs.rmi_list = new_rmi_list
new_inputs = inputs
else:
new_inputs = TableInput(new_rmi_list, inputs.exi_graph,
inputs.table)
return new_inputs
def purge_ensure_one_annot_per_images(ibs):
"""
pip install Pipe
"""
# Purge all but one annotation
images = ibs.images()
# images.aids
groups = images._annot_groups
import numpy as np
# Take all but the largest annotations per images
large_masks = [
ut.index_to_boolmask([np.argmax(x)], len(x)) for x in groups.bbox_area
]
small_masks = ut.lmap(ut.not_list, large_masks)
# Remove all but the largets annotation
small_aids = ut.zipcompress(groups.aid, small_masks)
small_aids = ut.flatten(small_aids)
# Fix any empty images
images = ibs.images()
empty_images = ut.where(np.array(images.num_annotations) == 0)
logger.info('empty_images = %r' % (empty_images, ))
# list(map(basename, map(dirname, images.uris_original)))
def VecPipe(func):
import pipe
@pipe.Pipe
def wrapped(sequence):
return map(func, sequence)
# return (None if item is None else func(item) for item in sequence)
return wrapped
name_list = list(images.uris_original | VecPipe(dirname)
| VecPipe(basename))
aids_list = images.aids
ut.assert_all_eq(list(aids_list | VecPipe(len)))
annots = ibs.annots(ut.flatten(aids_list))
annots.names = name_list
def add_annotmatch_undirected(ibs, aids1, aids2, **kwargs):
if len(aids1) == 0 and len(aids2) == 0:
return []
edges = list(zip(aids1, aids2))
from ibeis.algo.graph import nx_utils as nxu
# Enforce new undirected constraint
edges = ut.estarmap(nxu.e_, edges)
aids1, aids2 = list(zip(*edges))
am_rowids = ibs.get_annotmatch_rowid_from_undirected_superkey(aids1, aids2)
idxs = ut.where([r is None for r in am_rowids])
# Check which ones are None
aids1_ = ut.take(aids1, idxs)
aids2_ = ut.take(aids2, idxs)
# Create anything that is None
am_rowids_ = ibs.add_annotmatch(aids2_, aids1_)
# Use the other rowid if found
for idx, rowid in zip(idxs, am_rowids_):
am_rowids[idx] = rowid
return am_rowids
def compress(self, flags):
idxs = ut.where(flags)
return self.take(idxs)
def fuzzy_find_colxs(self, pat):
import utool as ut
colxs = ut.where(
ut.filterflags_general_tags(self.header_tags, in_any=[pat]))
return colxs
def get_col(table, tbl_rowids, colnames=None):
"""
colnames = ('mask', 'size')
FIXME; unpacking is confusing with sql controller
"""
# print('Get prop of %r, colnames=%r' % (table, colnames))
try:
request_unpack = False
if colnames is None:
colnames = table.data_colnames
#table._internal_data_colnames
else:
if isinstance(colnames, six.text_type):
request_unpack = True
colnames = (colnames,)
# print('* colnames = %r' % (colnames,))
eager = True
nInput = None
total = 0
intern_colnames = []
extern_resolve_colxs = []
nesting_xs = []
for c in colnames:
if c in table.external_to_internal:
intern_colnames.append([table.external_to_internal[c]])
read_func = table.extern_read_funcs[c]
extern_resolve_colxs.append((total, read_func))
nesting_xs.append(total)
total += 1
elif c in table.nested_to_flat:
nest = table.nested_to_flat[c]
nesting_xs.append(list(range(total, total + len(nest))))
intern_colnames.append(nest)
total += len(nest)
else:
nesting_xs.append(total)
intern_colnames.append([c])
total += 1
flat_intern_colnames = tuple(ut.flatten(intern_colnames))
# do sql read
# FIXME: understand unpack_scalars and keepwrap
raw_prop_list = table.get_internal_columns(
tbl_rowids, flat_intern_colnames, eager, nInput,
unpack_scalars=True, keepwrap=True)
# unpack_scalars=not
# request_unpack)
# print('depth(raw_prop_list) = %r' % (ut.depth_profile(raw_prop_list),))
prop_listT = list(zip(*raw_prop_list))
for extern_colx, read_func in extern_resolve_colxs:
data_list = []
for uri in prop_listT[extern_colx]:
try:
# FIXME: only do this for a localpath
uri1 = ut.unixjoin(table.depc.cache_dpath, uri)
data = read_func(uri1)
except Exception as ex:
ut.printex(ex, 'failed to load external data', iswarning=False)
raise
# FIXME
#data = None
data_list.append(data)
prop_listT[extern_colx] = data_list
nested_proplistT = ut.list_unflat_take(prop_listT, nesting_xs)
for tx in ut.where([isinstance(xs, list) for xs in nesting_xs]):
nested_proplistT[tx] = list(zip(*nested_proplistT[tx]))
prop_list = list(zip(*nested_proplistT))
if request_unpack:
prop_list = [None if p is None else p[0] for p in prop_list]
except Exception as ex:
ut.printex(ex, 'failed in get col', keys=[
'table.tablename',
'request_unpack',
'tbl_rowids',
'colnames',
'raw_prop_list',
(ut.depth_profile, 'raw_prop_list'),
'prop_listT',
(ut.depth_profile, 'prop_listT'),
'nesting_xs',
'nested_proplistT',
'prop_list'])
raise
return prop_list
def add_rows_from_parent(table, parent_rowids, config=None, verbose=True,
return_num_dirty=False):
"""
Lazy addition
"""
try:
# Get requested configuration id
config_rowid = table.get_config_rowid(config)
# Find leaf rowids that need to be computed
initial_rowid_list = table._get_rowid_from_superkey(parent_rowids,
config=config)
# Get corresponding "dirty" parent rowids
isdirty_list = ut.flag_None_items(initial_rowid_list)
dirty_parent_rowids = ut.compress(parent_rowids, isdirty_list)
num_dirty = len(dirty_parent_rowids)
num_total = len(parent_rowids)
if num_dirty > 0:
if verbose:
fmtstr = 'adding %d / %d new props to %r for config_rowid=%r'
print(fmtstr % (num_dirty, num_total, table.tablename,
config_rowid))
args = zip(*dirty_parent_rowids)
if table._asobject:
# Convinience
args = [table.depc.get_obj(parent, rowids)
for parent, rowids in zip(table.parents, args)]
# CALL EXTERNAL PREPROCESSING / GENERATION FUNCTION
proptup_gen = table.preproc_func(table.depc, *args, config=config)
#proptup_gen = list(proptup_gen)
if len(table._nested_idxs) > 0:
# TODO: rewrite
nested_nCols = len(table.data_colnames)
idxs1 = table._nested_idxs
mask1 = ut.index_to_boolmask(idxs1, nested_nCols)
mask2 = ut.not_list(mask1)
idxs2 = ut.where(mask2)
def unnest_data(data):
unnested_cols = list(zip(ut.take(data, idxs2)))
nested_cols = ut.take(data, idxs1)
grouped_items = [nested_cols, unnested_cols]
groupxs = [idxs1, idxs2]
unflat = ut.ungroup(grouped_items, groupxs, nested_nCols - 1)
return tuple(ut.flatten(unflat))
# Hack when a sql schema has tuples defined in it
proptup_gen = (unnest_data(data) for data in proptup_gen)
#proptup_gen = list(proptup_gen)
dirty_params_iter = (
parent_rowids + (config_rowid,) + data_cols
for parent_rowids, data_cols in zip(dirty_parent_rowids, proptup_gen))
#dirty_params_iter = list(dirty_params_iter)
#print('dirty_params_iter = %s' % (ut.repr2(dirty_params_iter, nl=1),))
CHUNKED_ADD = table.chunksize is not None
if CHUNKED_ADD:
for dirty_params_chunk in ut.ichunks(dirty_params_iter,
chunksize=table.chunksize):
table.db._add(table.tablename, table._table_colnames,
dirty_params_chunk,
nInput=len(dirty_params_chunk))
else:
nInput = num_dirty
table.db._add(table.tablename, table._table_colnames,
dirty_params_iter, nInput=nInput)
# Now that the dirty params are added get the correct order of rowids
rowid_list = table._get_rowid_from_superkey(parent_rowids,
config=config)
else:
rowid_list = initial_rowid_list
if return_num_dirty:
return rowid_list, num_dirty
else:
return rowid_list
except Exception as ex:
ut.printex(ex, 'error in add_rowids', keys=[
'table', 'parent_rowids', 'config', 'args',
'dirty_parent_rowids', 'table.preproc_func'])
raise
def convert_hsdb_to_ibeis(hsdir, dbdir=None, **kwargs):
r"""
Args
hsdir (str): Directory to folder *containing* _hsdb
dbdir (str): Output directory (defaults to same as hsdb)
CommandLine:
python -m ibeis convert_hsdb_to_ibeis --dbdir ~/work/Frogs
python -m ibeis convert_hsdb_to_ibeis --hsdir "/raid/raw/RotanTurtles/Roatan HotSpotter Nov_21_2016"
Ignore:
from ibeis.dbio.ingest_hsdb import * # NOQA
hsdir = "/raid/raw/RotanTurtles/Roatan HotSpotter Nov_21_2016"
dbdir = "~/work/RotanTurtles"
Example:
>>> # SCRIPT
>>> from ibeis.dbio.ingest_hsdb import * # NOQA
>>> dbdir = ut.get_argval('--dbdir', type_=str, default=None)
>>> hsdir = ut.get_argval('--hsdir', type_=str, default=dbdir)
>>> result = convert_hsdb_to_ibeis(hsdir)
>>> print(result)
"""
from ibeis.control import IBEISControl
import utool as ut
if dbdir is None:
dbdir = hsdir
print('[ingest] Ingesting hsdb: %r -> %r' % (hsdir, dbdir))
assert is_hsdb(
hsdir
), 'not a hotspotter database. cannot even force convert: hsdir=%r' % (
hsdir, )
assert not is_succesful_convert(dbdir), 'hsdir=%r is already converted' % (
hsdir, )
#print('FORCE DELETE: %r' % (hsdir,))
#ibsfuncs.delete_ibeis_database(hsdir)
imgdir = join(hsdir, 'images')
internal_dir = get_hsinternal(hsdir)
nametbl_fpath = join(internal_dir, 'name_table.csv')
imgtbl_fpath = join(internal_dir, 'image_table.csv')
chiptbl_fpath = join(internal_dir, 'chip_table.csv')
# READ NAME TABLE
name_text_list = ['____']
name_hs_nid_list = [0]
with open(nametbl_fpath, 'r') as nametbl_file:
name_reader = csv.reader(nametbl_file)
for ix, row in enumerate(name_reader):
#if ix >= 3:
if len(row) == 0 or row[0].strip().startswith('#'):
continue
else:
hs_nid = int(row[0])
name = row[1].strip()
name_text_list.append(name)
name_hs_nid_list.append(hs_nid)
# READ IMAGE TABLE
iamge_hs_gid_list = []
image_gname_list = []
image_reviewed_list = []
with open(imgtbl_fpath, 'r') as imgtb_file:
image_reader = csv.reader(imgtb_file)
for ix, row in enumerate(image_reader):
if len(row) == 0 or row[0].strip().startswith('#'):
continue
else:
hs_gid = int(row[0])
gname_ = row[1].strip()
# aif in hotspotter is equivilant to reviewed in IBEIS
reviewed = bool(row[2])
iamge_hs_gid_list.append(hs_gid)
image_gname_list.append(gname_)
image_reviewed_list.append(reviewed)
image_gpath_list = [join(imgdir, gname) for gname in image_gname_list]
ut.debug_duplicate_items(image_gpath_list)
#print(image_gpath_list)
image_exist_flags = list(map(exists, image_gpath_list))
missing_images = []
for image_gpath, flag in zip(image_gpath_list, image_exist_flags):
if not flag:
missing_images.append(image_gpath)
print('Image does not exist: %s' % image_gpath)
if not all(image_exist_flags):
print('Only %d / %d image exist' %
(sum(image_exist_flags), len(image_exist_flags)))
SEARCH_FOR_IMAGES = False
if SEARCH_FOR_IMAGES:
# Hack to try and find the missing images
from os.path import basename
subfiles = ut.glob(hsdir,
'*',
recursive=True,
fullpath=True,
with_files=True)
basename_to_existing = ut.group_items(subfiles,
ut.lmap(basename, subfiles))
can_copy_list = []
for gpath in missing_images:
gname = basename(gpath)
if gname not in basename_to_existing:
print('gname = %r' % (gname, ))
pass
else:
existing = basename_to_existing[gname]
can_choose = True
if len(existing) > 1:
if not ut.allsame(ut.lmap(ut.get_file_uuid, existing)):
can_choose = False
if can_choose:
found = existing[0]
can_copy_list.append((found, gpath))
else:
print(existing)
src, dst = ut.listT(can_copy_list)
ut.copy_list(src, dst)
# READ CHIP TABLE
chip_bbox_list = []
chip_theta_list = []
chip_hs_nid_list = []
chip_hs_gid_list = []
chip_note_list = []
with open(chiptbl_fpath, 'r') as chiptbl_file:
chip_reader = csv.reader(chiptbl_file)
for ix, row in enumerate(chip_reader):
if len(row) == 0 or row[0].strip().startswith('#'):
continue
else:
hs_gid = int(row[1])
hs_nid = int(row[2])
bbox_text = row[3]
theta = float(row[4])
notes = '<COMMA>'.join([item.strip() for item in row[5:]])
bbox_text = bbox_text.replace('[', '').replace(']', '').strip()
bbox_text = re.sub(' *', ' ', bbox_text)
bbox_strlist = bbox_text.split(' ')
bbox = tuple(map(int, bbox_strlist))
#bbox = [int(item) for item in bbox_strlist]
chip_hs_nid_list.append(hs_nid)
chip_hs_gid_list.append(hs_gid)
chip_bbox_list.append(bbox)
chip_theta_list.append(theta)
chip_note_list.append(notes)
names = ut.ColumnLists({
'hs_nid': name_hs_nid_list,
'text': name_text_list,
})
images = ut.ColumnLists({
'hs_gid': iamge_hs_gid_list,
'gpath': image_gpath_list,
'reviewed': image_reviewed_list,
'exists': image_exist_flags,
})
chips = ut.ColumnLists({
'hs_gid': chip_hs_gid_list,
'hs_nid': chip_hs_nid_list,
'bbox': chip_bbox_list,
'theta': chip_theta_list,
'note': chip_note_list,
})
IGNORE_MISSING_IMAGES = True
if IGNORE_MISSING_IMAGES:
# Ignore missing information
print('pre')
print('chips = %r' % (chips, ))
print('images = %r' % (images, ))
print('names = %r' % (names, ))
missing_gxs = ut.where(ut.not_list(images['exists']))
missing_gids = ut.take(images['hs_gid'], missing_gxs)
gid_to_cxs = ut.dzip(*chips.group_indicies('hs_gid'))
missing_cxs = ut.flatten(ut.take(gid_to_cxs, missing_gids))
# Remove missing images and dependant chips
images = images.remove(missing_gxs)
chips = chips.remove(missing_cxs)
valid_nids = set(chips['hs_nid'] + [0])
isvalid = [nid in valid_nids for nid in names['hs_nid']]
names = names.compress(isvalid)
print('post')
print('chips = %r' % (chips, ))
print('images = %r' % (images, ))
print('names = %r' % (names, ))
assert all(images['exists']), 'some images dont exist'
# if gid is None:
# print('Not adding the ix=%r-th Chip. Its image is corrupted image.' % (ix,))
# # continue
# # Build mappings to new indexes
# names_nid_to_nid = {names_nid: nid for (names_nid, nid) in zip(hs_nid_list, nid_list)}
# names_nid_to_nid[1] = names_nid_to_nid[0] # hsdb unknknown is 0 or 1
# images_gid_to_gid = {images_gid: gid for (images_gid, gid) in zip(hs_gid_list, gid_list)}
ibs = IBEISControl.request_IBEISController(dbdir=dbdir,
check_hsdb=False,
**kwargs)
assert len(ibs.get_valid_gids()) == 0, 'target database is not empty'
# Add names, images, and annotations
names['ibs_nid'] = ibs.add_names(names['text'])
images['ibs_gid'] = ibs.add_images(
images['gpath']) # any failed gids will be None
if True:
# Remove corrupted images
print('pre')
print('chips = %r' % (chips, ))
print('images = %r' % (images, ))
print('names = %r' % (names, ))
missing_gxs = ut.where(ut.flag_None_items(images['ibs_gid']))
missing_gids = ut.take(images['hs_gid'], missing_gxs)
gid_to_cxs = ut.dzip(*chips.group_indicies('hs_gid'))
missing_cxs = ut.flatten(ut.take(gid_to_cxs, missing_gids))
# Remove missing images and dependant chips
chips = chips.remove(missing_cxs)
images = images.remove(missing_gxs)
print('post')
print('chips = %r' % (chips, ))
print('images = %r' % (images, ))
print('names = %r' % (names, ))
# Index chips using new ibs rowids
ibs_gid_lookup = ut.dzip(images['hs_gid'], images['ibs_gid'])
ibs_nid_lookup = ut.dzip(names['hs_nid'], names['ibs_nid'])
try:
chips['ibs_gid'] = ut.take(ibs_gid_lookup, chips['hs_gid'])
except KeyError:
chips['ibs_gid'] = [
ibs_gid_lookup.get(index, None) for index in chips['hs_gid']
]
try:
chips['ibs_nid'] = ut.take(ibs_nid_lookup, chips['hs_nid'])
except KeyError:
chips['ibs_nid'] = [
ibs_nid_lookup.get(index, None) for index in chips['hs_nid']
]
ibs.add_annots(chips['ibs_gid'],
bbox_list=chips['bbox'],
theta_list=chips['theta'],
nid_list=chips['ibs_nid'],
notes_list=chips['note'])
# aid_list = ibs.get_valid_aids()
# flag_list = [True] * len(aid_list)
# ibs.set_annot_exemplar_flags(aid_list, flag_list)
# assert(all(ibs.get_annot_exemplar_flags(aid_list))), 'exemplars not set correctly'
# Write file flagging successful conversion
with open(join(ibs.get_ibsdir(), SUCCESS_FLAG_FNAME), 'w') as file_:
file_.write('Successfully converted hsdir=%r' % (hsdir, ))
print('finished ingest')
return ibs
def fuzzy_find_colxs(self, pat):
import utool as ut
colxs = ut.where(ut.filterflags_general_tags(self.header_tags, in_any=[pat]))
return colxs
