def preload_args_process(args):
from hscom import helpers
import sys
# Process relevant args
cids = args.query
if args.vdd:
helpers.vd(args.dbdir)
args.vdd = False
load_all = args.autoquery or len(cids) > 0
if helpers.inIPython() or '--cmd' in sys.argv:
args.nosteal = True
return load_all, cids
def load_csv_tables(db_dir, allow_new_dir=True):
'''
Big function which loads the csv tables from a datatabase directory
Returns HotspotterDirs and HotspotterTables
'''
if 'vdd' in sys.argv:
helpers.vd(db_dir)
print('\n=============================')
print('[ld2] Loading hotspotter csv tables: %r' % db_dir)
print('=============================')
hs_dirs = ds.HotspotterDirs(db_dir)
hs_tables = ds.HotspotterTables()
#exec(hs_dirs.execstr('hs_dirs'))
#print(hs_dirs.execstr('hs_dirs'))
img_dir = hs_dirs.img_dir
internal_dir = hs_dirs.internal_dir
db_dir = hs_dirs.db_dir
# --- Table Names ---
chip_table = join(internal_dir, CHIP_TABLE_FNAME)
name_table = join(internal_dir, NAME_TABLE_FNAME)
image_table = join(internal_dir, IMAGE_TABLE_FNAME) # TODO: Make optional
# --- CHECKS ---
has_dbdir = helpers.checkpath(db_dir)
has_imgdir = helpers.checkpath(img_dir)
has_chiptbl = helpers.checkpath(chip_table)
has_nametbl = helpers.checkpath(name_table)
has_imgtbl = helpers.checkpath(image_table)
# ChipTable Header Markers
header_numdata = '# NumData '
header_csvformat_re = '# *ChipID,'
v12_csvformat_re = r'#[0-9]*\) '
# Default ChipTable Header Variables
chip_csv_format = ['ChipID', 'ImgID', 'NameID', 'roi[tl_x tl_y w h]', 'theta']
v12_csv_format = ['instance_id', 'image_id', 'name_id', 'roi']
# TODO DETECT OLD FORMATS HERE
db_version = 'current'
isCurrentVersion = all([has_dbdir, has_imgdir, has_chiptbl, has_nametbl, has_imgtbl])
print('[ld2] isCurrentVersion=%r' % isCurrentVersion)
IS_VERSION_1_OR_2 = False
if not isCurrentVersion:
helpers.checkpath(db_dir, verbose=True)
helpers.checkpath(img_dir, verbose=True)
helpers.checkpath(chip_table, verbose=True)
helpers.checkpath(name_table, verbose=True)
helpers.checkpath(image_table, verbose=True)
import db_info
def assign_alternate(tblname):
path = join(db_dir, tblname)
if helpers.checkpath(path, verbose=True):
return path
path = join(db_dir, '.hs_internals', tblname)
if helpers.checkpath(path, verbose=True):
return path
raise Exception('bad state=%r' % tblname)
#
if db_info.has_v2_gt(db_dir):
IS_VERSION_1_OR_2 = True
db_version = 'hotspotter-v2'
chip_csv_format = []
header_csvformat_re = v12_csvformat_re
chip_table = assign_alternate('instance_table.csv')
name_table = assign_alternate('name_table.csv')
image_table = assign_alternate('image_table.csv')
#
elif db_info.has_v1_gt(db_dir):
IS_VERSION_1_OR_2 = True
db_version = 'hotspotter-v1'
chip_csv_format = []
header_csvformat_re = v12_csvformat_re
chip_table = assign_alternate('animal_info_table.csv')
name_table = assign_alternate('name_table.csv')
image_table = assign_alternate('image_table.csv')
#
elif db_info.has_ss_gt(db_dir):
db_version = 'stripespotter'
chip_table = join(db_dir, 'SightingData.csv')
chip_csv_format = ['imgindex', 'original_filepath', 'roi', 'animal_name']
header_csvformat_re = '#imgindex,'
#raise NotImplementedError('stripe spotter conversion')
if not helpers.checkpath(chip_table, verbose=True):
raise Exception('bad state chip_table=%r' % chip_table)
else:
try:
db_version = 'current' # Well almost
chip_table = assign_alternate(CHIP_TABLE_FNAME)
name_table = assign_alternate(NAME_TABLE_FNAME)
image_table = assign_alternate(IMAGE_TABLE_FNAME)
except Exception:
if db_info.has_partial_gt(db_dir):
print('[ld2] detected incomplete database')
raise NotImplementedError('partial database recovery')
elif allow_new_dir:
print('[ld2] detected new dir')
hs_dirs.ensure_dirs()
return hs_dirs, hs_tables, 'newdb'
else:
import traceback
print(traceback.format_exc())
print('[ld2] I AM IN A BAD STATE!')
errmsg = ''
errmsg += ('\n\n!!!!!\n\n')
errmsg += (' ! The data tables seem to not be loaded')
errmsg += (' Files in internal dir: %r' % internal_dir)
for fname in os.listdir(internal_dir):
errmsg += (' ! fname')
errmsg += ('\n\n!!!!!\n\n')
print(errmsg)
raise Exception(errmsg)
if not helpers.checkpath(chip_table):
raise Exception('bad state chip_table=%r' % chip_table)
print('[ld2] detected %r' % db_version)
hs_dirs.ensure_dirs()
print('-------------------------')
print('[ld2] Loading database tables: ')
cid_lines = []
line_num = 0
csv_line = ''
csv_fields = []
# RCOS TODO: We need a more general csv read function
# which can handle all of these little corner cases delt with here.
try:
# ------------------
# --- READ NAMES ---
# ------------------
print('[ld2] Loading name table: %r' % name_table)
nx2_name = [UNKNOWN_NAME, UNKNOWN_NAME]
nid2_nx = {0: 0, 1: 1}
name_lines = open(name_table, 'r')
for line_num, csv_line in enumerate(name_lines):
csv_line = csv_line.strip('\n\r\t ')
if len(csv_line) == 0 or csv_line.find('#') == 0:
continue
csv_fields = [_.strip(' ') for _ in csv_line.strip('\n\r ').split(',')]
nid = int(csv_fields[0])
name = csv_fields[1]
nid2_nx[nid] = len(nx2_name)
nx2_name.append(name)
name_lines.close()
if VERBOSE_LOAD_DATA:
print('[ld2] * Loaded %r names (excluding unknown names)' % (len(nx2_name) - 2))
print('[ld2] * Done loading name table')
except IOError as ex:
print('IOError: %r' % ex)
print('[ld2.name] loading without name table')
#raise
except Exception as ex:
print('[ld2.name] ERROR %r' % ex)
#print('[ld2.name] ERROR name_tbl parsing: %s' % (''.join(cid_lines)))
print('[ld2.name] ERROR on line number: %r' % (line_num))
print('[ld2.name] ERROR on line: %r' % (csv_line))
print('[ld2.name] ERROR on fields: %r' % (csv_fields))
try:
# -------------------
# --- READ IMAGES ---
# -------------------
gx2_gname = []
gx2_aif = []
gid2_gx = {} # this is not used. It can probably be removed
def add_image(gname, aif, gid):
gx = len(gx2_gname)
gx2_gname.append(gname)
gx2_aif.append(aif)
if gid is not None:
# this is not used. It can probably be removed
gid2_gx[gid] = gx
print('[ld2] Loading images')
# Load Image Table
# <LEGACY CODE>
if VERBOSE_LOAD_DATA:
print('[ld2] * Loading image table: %r' % image_table)
gid_lines = open(image_table, 'r').readlines()
for line_num, csv_line in enumerate(gid_lines):
csv_line = csv_line.strip('\n\r\t ')
if len(csv_line) == 0 or csv_line.find('#') == 0:
continue
csv_fields = [_.strip(' ') for _ in csv_line.strip('\n\r ').split(',')]
gid = int(csv_fields[0])
# You have 3 csv files. Format == gid, gname.ext, aif
if len(csv_fields) == 3:
gname = csv_fields[1]
aif = csv_fields[2].lower() in ['true', '1'] # convert to bool correctly
# You have 4 csv fields. Format == gid, gname, ext, aif
if len(csv_fields) == 4:
gname = '.'.join(csv_fields[1:3])
aif = csv_fields[3].lower() in ['true', '1']
add_image(gname, aif, gid)
nTableImgs = len(gx2_gname)
fromTableNames = set(gx2_gname)
if VERBOSE_LOAD_DATA:
print('[ld2] * table specified %r images' % nTableImgs)
# </LEGACY CODE>
# Load Image Directory
print('[ld2] * Loading image directory: %r' % img_dir)
nDirImgs = 0
nDirImgsAlready = 0
for fname in os.listdir(img_dir):
if len(fname) > 4 and fname[-4:].lower() in ['.jpg', '.png', '.tiff']:
if fname in fromTableNames:
nDirImgsAlready += 1
continue
add_image(fname, False, None)
nDirImgs += 1
if VERBOSE_LOAD_DATA:
print('[ld2] * dir specified %r images' % nDirImgs)
print('[ld2] * %r were already specified in the table' % nDirImgsAlready)
print('[ld2] * Loaded %r images' % len(gx2_gname))
print('[ld2] * Done loading images')
except IOError:
print('IOError: %r' % ex)
print('[ld2.img] loading without image table')
#raise
except Exception as ex:
print('[ld2!.img] ERROR %r' % ex)
#print('[ld2.img] ERROR image_tbl parsing: %s' % (''.join(cid_lines)))
print('[ld2!.img] ERROR on line number: %r' % (line_num))
print('[ld2!.img] ERROR on line: %r' % (csv_line))
print('[ld2!.img] ERROR on fields: %r' % (csv_fields))
raise
try:
# ------------------
# --- READ CHIPS ---
# ------------------
print('[ld2] Loading chip table: %r' % chip_table)
# Load Chip Table Header
cid_lines = open(chip_table, 'r').readlines()
num_data = -1
# Parse Chip Table Header
for line_num, csv_line in enumerate(cid_lines):
#print('[LINE %4d] %r' % (line_num, csv_line))
csv_line = csv_line.strip('\n\r\t ')
if len(csv_line) == 0:
#print('[LINE %4d] BROKEN' % (line_num))
continue
csv_line = csv_line.strip('\n')
if csv_line.find('#') != 0:
#print('[LINE %4d] BROKEN' % (line_num))
break # Break after header
if re.search(header_csvformat_re, csv_line) is not None:
#print('[LINE %4d] SEARCH' % (line_num))
# Specified Header Variables
if IS_VERSION_1_OR_2:
#print(csv_line)
end_ = csv_line.find('-')
if end_ != -1:
end_ = end_ - 1
#print('end_=%r' % end_)
fieldname = csv_line[5:end_]
else:
fieldname = csv_line[5:]
#print(fieldname)
chip_csv_format += [fieldname]
else:
chip_csv_format = [_.strip() for _ in csv_line.strip('#').split(',')]
#print('[ld2] read chip_csv_format: %r' % chip_csv_format)
if csv_line.find(header_numdata) == 0:
#print('[LINE %4d] NUM_DATA' % (line_num))
num_data = int(csv_line.replace(header_numdata, ''))
if IS_VERSION_1_OR_2 and len(chip_csv_format) == 0:
chip_csv_format = v12_csv_format
if VERBOSE_LOAD_DATA:
print('[ld2] * num_chips: %r' % num_data)
print('[ld2] * chip_csv_format: %r ' % chip_csv_format)
#print('[ld2.chip] Header Columns: %s\n ' % '\n '.join(chip_csv_format))
cid_x = tryindex(chip_csv_format, 'ChipID', 'imgindex', 'instance_id')
gid_x = tryindex(chip_csv_format, 'ImgID', 'image_id')
nid_x = tryindex(chip_csv_format, 'NameID', 'name_id')
roi_x = tryindex(chip_csv_format, 'roi[tl_x tl_y w h]', 'roi')
theta_x = tryindex(chip_csv_format, 'theta')
# new fields
gname_x = tryindex(chip_csv_format, 'Image', 'original_filepath')
name_x = tryindex(chip_csv_format, 'Name', 'animal_name')
required_x = [cid_x, gid_x, gname_x, nid_x, name_x, roi_x, theta_x]
# Hotspotter Chip Tables
cx2_cid = []
cx2_nx = []
cx2_gx = []
cx2_roi = []
cx2_theta = []
# x is a csv field index in this context
# get csv indexes which are unknown properties
prop_x_list = np.setdiff1d(range(len(chip_csv_format)), required_x).tolist()
px2_prop_key = [chip_csv_format[x] for x in prop_x_list]
prop_dict = {}
for prop in iter(px2_prop_key):
prop_dict[prop] = []
if VERBOSE_LOAD_DATA:
print('[ld2] * num_user_properties: %r' % (len(prop_dict.keys())))
# Parse Chip Table
for line_num, csv_line in enumerate(cid_lines):
csv_line = csv_line.strip('\n\r\t ')
if len(csv_line) == 0 or csv_line.find('#') == 0:
continue
csv_fields = [_.strip(' ') for _ in csv_line.strip('\n\r ').split(',')]
#
# Load Chip ID
try:
cid = int(csv_fields[cid_x])
except ValueError:
print('[ld2!] cid_x = %r' % cid_x)
print('[ld2!] csv_fields = %r' % csv_fields)
print('[ld2!] csv_fields[cid_x] = %r' % csv_fields[cid_x])
print(chip_csv_format)
raise
#
# Load Chip ROI Info
if roi_x != -1:
roi_str = csv_fields[roi_x].strip('[').strip(']')
roi = [int(round(float(_))) for _ in roi_str.split()]
#
# Load Chip theta Info
if theta_x != -1:
theta = float(csv_fields[theta_x])
else:
theta = 0
#
# Load Image ID/X
if gid_x != -1:
gid = int(csv_fields[gid_x])
gx = gid2_gx[gid]
elif gname_x != -1:
gname = csv_fields[gname_x]
if db_version == 'stripespotter':
if not exists(gname):
gname = 'img-%07d.jpg' % cid
gpath = join(db_dir, 'images', gname)
w, h = Image.open(gpath).size
roi = [1, 1, w, h]
try:
gx = gx2_gname.index(gname)
except ValueError:
gx = len(gx2_gname)
gx2_gname.append(gname)
#
# Load Name ID/X
if nid_x != -1:
#print('namedbg csv_fields=%r' % csv_fields)
#print('namedbg nid_x = %r' % nid_x)
nid = int(csv_fields[nid_x])
#print('namedbg %r' % nid)
nx = nid2_nx[nid]
elif name_x != -1:
name = csv_fields[name_x]
try:
nx = nx2_name.index(name)
except ValueError:
nx = len(nx2_name)
nx2_name.append(name)
# Append info to cid lists
cx2_cid.append(cid)
cx2_gx.append(gx)
cx2_nx.append(nx)
cx2_roi.append(roi)
cx2_theta.append(theta)
for px, x in enumerate(prop_x_list):
prop = px2_prop_key[px]
prop_val = csv_fields[x]
prop_dict[prop].append(prop_val)
except Exception as ex:
print('[chip.ld2] ERROR %r' % ex)
#print('[chip.ld2] ERROR parsing: %s' % (''.join(cid_lines)))
print('[chip.ld2] ERROR reading header: %r' % (line_num))
print('[chip.ld2] ERROR on line number: %r' % (line_num))
print('[chip.ld2] ERROR on line: %r' % (csv_line))
print('[chip.ld2] ERROR on fields: %r' % (csv_fields))
raise
if VERBOSE_LOAD_DATA:
print('[ld2] * Loaded: %r chips' % (len(cx2_cid)))
print('[ld2] * Done loading chip table')
# Return all information from load_tables
#hs_tables.gid2_gx = gid2_gx
#hs_tables.nid2_nx = nid2_nx
hs_tables.init(gx2_gname, gx2_aif,
nx2_name,
cx2_cid, cx2_nx, cx2_gx,
cx2_roi, cx2_theta, prop_dict)
print('[ld2] Done Loading hotspotter csv tables: %r' % (db_dir))
if 'vcd' in sys.argv:
helpers.vd(hs_dirs.computed_dir)
return hs_dirs, hs_tables, db_version
def vrd(hs):
result_dir = os.path.normpath(hs.dirs.result_dir)
print('[hs] viewing result_dir: %r ' % result_dir)
helpers.vd(result_dir)
def vdg(hs):
output_dir = get_training_output_dir(hs)
helpers.vd(output_dir)
def vcd(hs):
computed_dir = os.path.normpath(hs.dirs.computed_dir)
print('[hs] viewing computed_dir: %r ' % computed_dir)
helpers.vd(computed_dir)
def vgd(hs):
global_dir = io.GLOBAL_CACHE_DIR
print('[hs] viewing global_dir: %r ' % global_dir)
helpers.vd(global_dir)
def vrd(hs):
result_dir = os.path.normpath(hs.dirs.result_dir)
print('[hs] viewing result_dir: %r ' % result_dir)
helpers.vd(result_dir)
def vdd(hs):
db_dir = os.path.normpath(hs.dirs.db_dir)
print('[hs] viewing db_dir: %r ' % db_dir)
helpers.vd(db_dir)
def vgd(hs):
global_dir = io.GLOBAL_CACHE_DIR
print('[hs] viewing global_dir: %r ' % global_dir)
helpers.vd(global_dir)
def vcd(hs):
computed_dir = os.path.normpath(hs.dirs.computed_dir)
print('[hs] viewing computed_dir: %r ' % computed_dir)
helpers.vd(computed_dir)
def vdd(hs):
db_dir = os.path.normpath(hs.dirs.db_dir)
print('[hs] viewing db_dir: %r ' % db_dir)
helpers.vd(db_dir)
def load_csv_tables(db_dir, allow_new_dir=True):
'''
Big function which loads the csv tables from a datatabase directory
Returns HotspotterDirs and HotspotterTables
'''
if 'vdd' in sys.argv:
helpers.vd(db_dir)
print('\n=============================')
print('[ld2] Loading hotspotter csv tables: %r' % db_dir)
print('=============================')
hs_dirs = ds.HotspotterDirs(db_dir)
hs_tables = ds.HotspotterTables()
#exec(hs_dirs.execstr('hs_dirs'))
#print(hs_dirs.execstr('hs_dirs'))
img_dir = hs_dirs.img_dir
internal_dir = hs_dirs.internal_dir
db_dir = hs_dirs.db_dir
# --- Table Names ---
chip_table = join(internal_dir, CHIP_TABLE_FNAME)
name_table = join(internal_dir, NAME_TABLE_FNAME)
image_table = join(internal_dir, IMAGE_TABLE_FNAME) # TODO: Make optional
# --- CHECKS ---
has_dbdir = helpers.checkpath(db_dir)
has_imgdir = helpers.checkpath(img_dir)
has_chiptbl = helpers.checkpath(chip_table)
has_nametbl = helpers.checkpath(name_table)
has_imgtbl = helpers.checkpath(image_table)
# ChipTable Header Markers
header_numdata = '# NumData '
header_csvformat_re = '# *ChipID,'
v12_csvformat_re = r'#[0-9]*\) '
# Default ChipTable Header Variables
chip_csv_format = [
'ChipID', 'ImgID', 'NameID', 'roi[tl_x tl_y w h]', 'theta'
]
v12_csv_format = ['instance_id', 'image_id', 'name_id', 'roi']
# TODO DETECT OLD FORMATS HERE
db_version = 'current'
isCurrentVersion = all(
[has_dbdir, has_imgdir, has_chiptbl, has_nametbl, has_imgtbl])
print('[ld2] isCurrentVersion=%r' % isCurrentVersion)
IS_VERSION_1_OR_2 = False
if not isCurrentVersion:
helpers.checkpath(db_dir, verbose=True)
helpers.checkpath(img_dir, verbose=True)
helpers.checkpath(chip_table, verbose=True)
helpers.checkpath(name_table, verbose=True)
helpers.checkpath(image_table, verbose=True)
import db_info
def assign_alternate(tblname):
path = join(db_dir, tblname)
if helpers.checkpath(path, verbose=True):
return path
path = join(db_dir, '.hs_internals', tblname)
if helpers.checkpath(path, verbose=True):
return path
raise Exception('bad state=%r' % tblname)
#
if db_info.has_v2_gt(db_dir):
IS_VERSION_1_OR_2 = True
db_version = 'hotspotter-v2'
chip_csv_format = []
header_csvformat_re = v12_csvformat_re
chip_table = assign_alternate('instance_table.csv')
name_table = assign_alternate('name_table.csv')
image_table = assign_alternate('image_table.csv')
#
elif db_info.has_v1_gt(db_dir):
IS_VERSION_1_OR_2 = True
db_version = 'hotspotter-v1'
chip_csv_format = []
header_csvformat_re = v12_csvformat_re
chip_table = assign_alternate('animal_info_table.csv')
name_table = assign_alternate('name_table.csv')
image_table = assign_alternate('image_table.csv')
#
elif db_info.has_ss_gt(db_dir):
db_version = 'stripespotter'
chip_table = join(db_dir, 'SightingData.csv')
chip_csv_format = [
'imgindex', 'original_filepath', 'roi', 'animal_name'
]
header_csvformat_re = '#imgindex,'
#raise NotImplementedError('stripe spotter conversion')
if not helpers.checkpath(chip_table, verbose=True):
raise Exception('bad state chip_table=%r' % chip_table)
else:
try:
db_version = 'current' # Well almost
chip_table = assign_alternate(CHIP_TABLE_FNAME)
name_table = assign_alternate(NAME_TABLE_FNAME)
image_table = assign_alternate(IMAGE_TABLE_FNAME)
except Exception:
if db_info.has_partial_gt(db_dir):
print('[ld2] detected incomplete database')
raise NotImplementedError('partial database recovery')
elif allow_new_dir:
print('[ld2] detected new dir')
hs_dirs.ensure_dirs()
return hs_dirs, hs_tables, 'newdb'
else:
import traceback
print(traceback.format_exc())
print('[ld2] I AM IN A BAD STATE!')
errmsg = ''
errmsg += ('\n\n!!!!!\n\n')
errmsg += (' ! The data tables seem to not be loaded')
errmsg += (' Files in internal dir: %r' % internal_dir)
for fname in os.listdir(internal_dir):
errmsg += (' ! fname')
errmsg += ('\n\n!!!!!\n\n')
print(errmsg)
raise Exception(errmsg)
if not helpers.checkpath(chip_table):
raise Exception('bad state chip_table=%r' % chip_table)
print('[ld2] detected %r' % db_version)
hs_dirs.ensure_dirs()
print('-------------------------')
print('[ld2] Loading database tables: ')
cid_lines = []
line_num = 0
csv_line = ''
csv_fields = []
# RCOS TODO: We need a more general csv read function
# which can handle all of these little corner cases delt with here.
try:
# ------------------
# --- READ NAMES ---
# ------------------
print('[ld2] Loading name table: %r' % name_table)
nx2_name = [UNKNOWN_NAME, UNKNOWN_NAME]
nid2_nx = {0: 0, 1: 1}
name_lines = open(name_table, 'r')
for line_num, csv_line in enumerate(name_lines):
csv_line = csv_line.strip('\n\r\t ')
if len(csv_line) == 0 or csv_line.find('#') == 0:
continue
csv_fields = [
_.strip(' ') for _ in csv_line.strip('\n\r ').split(',')
]
nid = int(csv_fields[0])
name = csv_fields[1]
nid2_nx[nid] = len(nx2_name)
nx2_name.append(name)
name_lines.close()
if VERBOSE_LOAD_DATA:
print('[ld2] * Loaded %r names (excluding unknown names)' %
(len(nx2_name) - 2))
print('[ld2] * Done loading name table')
except IOError as ex:
print('IOError: %r' % ex)
print('[ld2.name] loading without name table')
#raise
except Exception as ex:
print('[ld2.name] ERROR %r' % ex)
#print('[ld2.name] ERROR name_tbl parsing: %s' % (''.join(cid_lines)))
print('[ld2.name] ERROR on line number: %r' % (line_num))
print('[ld2.name] ERROR on line: %r' % (csv_line))
print('[ld2.name] ERROR on fields: %r' % (csv_fields))
try:
# -------------------
# --- READ IMAGES ---
# -------------------
gx2_gname = []
gx2_aif = []
gid2_gx = {} # this is not used. It can probably be removed
def add_image(gname, aif, gid):
gx = len(gx2_gname)
gx2_gname.append(gname)
gx2_aif.append(aif)
if gid is not None:
# this is not used. It can probably be removed
gid2_gx[gid] = gx
print('[ld2] Loading images')
# Load Image Table
# <LEGACY CODE>
if VERBOSE_LOAD_DATA:
print('[ld2] * Loading image table: %r' % image_table)
gid_lines = open(image_table, 'r').readlines()
for line_num, csv_line in enumerate(gid_lines):
csv_line = csv_line.strip('\n\r\t ')
if len(csv_line) == 0 or csv_line.find('#') == 0:
continue
csv_fields = [
_.strip(' ') for _ in csv_line.strip('\n\r ').split(',')
]
gid = int(csv_fields[0])
# You have 3 csv files. Format == gid, gname.ext, aif
if len(csv_fields) == 3:
gname = csv_fields[1]
aif = csv_fields[2].lower() in ['true', '1'
] # convert to bool correctly
# You have 4 csv fields. Format == gid, gname, ext, aif
if len(csv_fields) == 4:
gname = '.'.join(csv_fields[1:3])
aif = csv_fields[3].lower() in ['true', '1']
add_image(gname, aif, gid)
nTableImgs = len(gx2_gname)
fromTableNames = set(gx2_gname)
if VERBOSE_LOAD_DATA:
print('[ld2] * table specified %r images' % nTableImgs)
# </LEGACY CODE>
# Load Image Directory
print('[ld2] * Loading image directory: %r' % img_dir)
nDirImgs = 0
nDirImgsAlready = 0
for fname in os.listdir(img_dir):
if len(fname) > 4 and fname[-4:].lower() in [
'.jpg', '.png', '.tiff'
]:
if fname in fromTableNames:
nDirImgsAlready += 1
continue
add_image(fname, False, None)
nDirImgs += 1
if VERBOSE_LOAD_DATA:
print('[ld2] * dir specified %r images' % nDirImgs)
print('[ld2] * %r were already specified in the table' %
nDirImgsAlready)
print('[ld2] * Loaded %r images' % len(gx2_gname))
print('[ld2] * Done loading images')
except IOError:
print('IOError: %r' % ex)
print('[ld2.img] loading without image table')
#raise
except Exception as ex:
print('[ld2!.img] ERROR %r' % ex)
#print('[ld2.img] ERROR image_tbl parsing: %s' % (''.join(cid_lines)))
print('[ld2!.img] ERROR on line number: %r' % (line_num))
print('[ld2!.img] ERROR on line: %r' % (csv_line))
print('[ld2!.img] ERROR on fields: %r' % (csv_fields))
raise
try:
# ------------------
# --- READ CHIPS ---
# ------------------
print('[ld2] Loading chip table: %r' % chip_table)
# Load Chip Table Header
cid_lines = open(chip_table, 'r').readlines()
num_data = -1
# Parse Chip Table Header
for line_num, csv_line in enumerate(cid_lines):
#print('[LINE %4d] %r' % (line_num, csv_line))
csv_line = csv_line.strip('\n\r\t ')
if len(csv_line) == 0:
#print('[LINE %4d] BROKEN' % (line_num))
continue
csv_line = csv_line.strip('\n')
if csv_line.find('#') != 0:
#print('[LINE %4d] BROKEN' % (line_num))
break # Break after header
if re.search(header_csvformat_re, csv_line) is not None:
#print('[LINE %4d] SEARCH' % (line_num))
# Specified Header Variables
if IS_VERSION_1_OR_2:
#print(csv_line)
end_ = csv_line.find('-')
if end_ != -1:
end_ = end_ - 1
#print('end_=%r' % end_)
fieldname = csv_line[5:end_]
else:
fieldname = csv_line[5:]
#print(fieldname)
chip_csv_format += [fieldname]
else:
chip_csv_format = [
_.strip() for _ in csv_line.strip('#').split(',')
]
#print('[ld2] read chip_csv_format: %r' % chip_csv_format)
if csv_line.find(header_numdata) == 0:
#print('[LINE %4d] NUM_DATA' % (line_num))
num_data = int(csv_line.replace(header_numdata, ''))
if IS_VERSION_1_OR_2 and len(chip_csv_format) == 0:
chip_csv_format = v12_csv_format
if VERBOSE_LOAD_DATA:
print('[ld2] * num_chips: %r' % num_data)
print('[ld2] * chip_csv_format: %r ' % chip_csv_format)
#print('[ld2.chip] Header Columns: %s\n ' % '\n '.join(chip_csv_format))
cid_x = tryindex(chip_csv_format, 'ChipID', 'imgindex', 'instance_id')
gid_x = tryindex(chip_csv_format, 'ImgID', 'image_id')
nid_x = tryindex(chip_csv_format, 'NameID', 'name_id')
roi_x = tryindex(chip_csv_format, 'roi[tl_x tl_y w h]', 'roi')
theta_x = tryindex(chip_csv_format, 'theta')
# new fields
gname_x = tryindex(chip_csv_format, 'Image', 'original_filepath')
name_x = tryindex(chip_csv_format, 'Name', 'animal_name')
required_x = [cid_x, gid_x, gname_x, nid_x, name_x, roi_x, theta_x]
# Hotspotter Chip Tables
cx2_cid = []
cx2_nx = []
cx2_gx = []
cx2_roi = []
cx2_theta = []
# x is a csv field index in this context
# get csv indexes which are unknown properties
prop_x_list = np.setdiff1d(range(len(chip_csv_format)),
required_x).tolist()
px2_prop_key = [chip_csv_format[x] for x in prop_x_list]
prop_dict = {}
for prop in iter(px2_prop_key):
prop_dict[prop] = []
if VERBOSE_LOAD_DATA:
print('[ld2] * num_user_properties: %r' % (len(prop_dict.keys())))
# Parse Chip Table
for line_num, csv_line in enumerate(cid_lines):
csv_line = csv_line.strip('\n\r\t ')
if len(csv_line) == 0 or csv_line.find('#') == 0:
continue
csv_fields = [
_.strip(' ') for _ in csv_line.strip('\n\r ').split(',')
]
#
# Load Chip ID
try:
cid = int(csv_fields[cid_x])
except ValueError:
print('[ld2!] cid_x = %r' % cid_x)
print('[ld2!] csv_fields = %r' % csv_fields)
print('[ld2!] csv_fields[cid_x] = %r' % csv_fields[cid_x])
print(chip_csv_format)
raise
#
# Load Chip ROI Info
if roi_x != -1:
roi_str = csv_fields[roi_x].strip('[').strip(']')
roi = [int(round(float(_))) for _ in roi_str.split()]
#
# Load Chip theta Info
if theta_x != -1:
theta = float(csv_fields[theta_x])
else:
theta = 0
#
# Load Image ID/X
if gid_x != -1:
gid = int(csv_fields[gid_x])
gx = gid2_gx[gid]
elif gname_x != -1:
gname = csv_fields[gname_x]
if db_version == 'stripespotter':
if not exists(gname):
gname = 'img-%07d.jpg' % cid
gpath = join(db_dir, 'images', gname)
w, h = Image.open(gpath).size
roi = [1, 1, w, h]
try:
gx = gx2_gname.index(gname)
except ValueError:
gx = len(gx2_gname)
gx2_gname.append(gname)
#
# Load Name ID/X
if nid_x != -1:
#print('namedbg csv_fields=%r' % csv_fields)
#print('namedbg nid_x = %r' % nid_x)
nid = int(csv_fields[nid_x])
#print('namedbg %r' % nid)
nx = nid2_nx[nid]
elif name_x != -1:
name = csv_fields[name_x]
try:
nx = nx2_name.index(name)
except ValueError:
nx = len(nx2_name)
nx2_name.append(name)
# Append info to cid lists
cx2_cid.append(cid)
cx2_gx.append(gx)
cx2_nx.append(nx)
cx2_roi.append(roi)
cx2_theta.append(theta)
for px, x in enumerate(prop_x_list):
prop = px2_prop_key[px]
prop_val = csv_fields[x]
prop_dict[prop].append(prop_val)
except Exception as ex:
print('[chip.ld2] ERROR %r' % ex)
#print('[chip.ld2] ERROR parsing: %s' % (''.join(cid_lines)))
print('[chip.ld2] ERROR reading header: %r' % (line_num))
print('[chip.ld2] ERROR on line number: %r' % (line_num))
print('[chip.ld2] ERROR on line: %r' % (csv_line))
print('[chip.ld2] ERROR on fields: %r' % (csv_fields))
raise
if VERBOSE_LOAD_DATA:
print('[ld2] * Loaded: %r chips' % (len(cx2_cid)))
print('[ld2] * Done loading chip table')
# Return all information from load_tables
#hs_tables.gid2_gx = gid2_gx
#hs_tables.nid2_nx = nid2_nx
hs_tables.init(gx2_gname, gx2_aif, nx2_name, cx2_cid, cx2_nx, cx2_gx,
cx2_roi, cx2_theta, prop_dict)
print('[ld2] Done Loading hotspotter csv tables: %r' % (db_dir))
if 'vcd' in sys.argv:
helpers.vd(hs_dirs.computed_dir)
return hs_dirs, hs_tables, db_version
def vdg(hs):
output_dir = get_training_output_dir(hs)
util.vd(output_dir)