def plot_keypoint_scales(hs, fnum=1):
print('[dev] plot_keypoint_scales()')
cx2_kpts = hs.feats.cx2_kpts
cx2_nFeats = map(len, cx2_kpts)
kpts = np.vstack(cx2_kpts)
print('[dev] --- LaTeX --- ')
_printopts = np.get_printoptions()
np.set_printoptions(precision=3)
print(pytex.latex_scalar(r'\# keypoints, ', len(kpts)))
print(pytex.latex_mystats(r'\# keypoints per image', cx2_nFeats))
acd = kpts[:, 2:5].T
scales = np.sqrt(acd[0] * acd[2])
scales = np.array(sorted(scales))
print(pytex.latex_mystats(r'keypoint scale', scales))
np.set_printoptions(**_printopts)
print('[dev] ---/LaTeX --- ')
#
df2.figure(fnum=fnum, docla=True, title='sorted scales')
df2.plot(scales)
df2.adjust_subplots_safe()
#ax = df2.gca()
#ax.set_yscale('log')
#ax.set_xscale('log')
#
fnum += 1
df2.figure(fnum=fnum, docla=True, title='hist scales')
df2.show_histogram(scales, bins=20)
df2.adjust_subplots_safe()
#ax = df2.gca()
#ax.set_yscale('log')
#ax.set_xscale('log')
return fnum
def plot_keypoint_scales(hs, fnum=1):
print('[dev] plot_keypoint_scales()')
cx2_kpts = hs.feats.cx2_kpts
cx2_nFeats = map(len, cx2_kpts)
kpts = np.vstack(cx2_kpts)
print('[dev] --- LaTeX --- ')
_printopts = np.get_printoptions()
np.set_printoptions(precision=3)
print(pytex.latex_scalar(r'\# keypoints, ', len(kpts)))
print(pytex.latex_mystats(r'\# keypoints per image', cx2_nFeats))
acd = kpts[:, 2:5].T
scales = np.sqrt(acd[0] * acd[2])
scales = np.array(sorted(scales))
print(pytex.latex_mystats(r'keypoint scale', scales))
np.set_printoptions(**_printopts)
print('[dev] ---/LaTeX --- ')
#
df2.figure(fnum=fnum, docla=True, title='sorted scales')
df2.plot(scales)
df2.adjust_subplots_safe()
#ax = df2.gca()
#ax.set_yscale('log')
#ax.set_xscale('log')
#
fnum += 1
df2.figure(fnum=fnum, docla=True, title='hist scales')
df2.show_histogram(scales, bins=20)
df2.adjust_subplots_safe()
#ax = df2.gca()
#ax.set_yscale('log')
#ax.set_xscale('log')
return fnum
def dbstats(hs):
# Chip / Name / Image stats
dbinfo_locals = db_info.db_info(hs)
db_name = hs.get_db_name(True)
#num_images = dbinfo_locals['num_images']
num_chips = dbinfo_locals['num_chips']
num_names = len(dbinfo_locals['valid_nxs'])
num_singlenames = len(dbinfo_locals['singleton_nxs'])
num_multinames = len(dbinfo_locals['multiton_nxs'])
num_multichips = len(dbinfo_locals['multiton_cxs'])
multiton_nx2_nchips = dbinfo_locals['multiton_nx2_nchips']
#tex_nImage = latex_formater.latex_scalar(r'\# images', num_images)
tex_nChip = latex_formater.latex_scalar(r'\# chips', num_chips)
tex_nName = latex_formater.latex_scalar(r'\# names', num_names)
tex_nSingleName = latex_formater.latex_scalar(r'\# singlenames',
num_singlenames)
tex_nMultiName = latex_formater.latex_scalar(r'\# multinames',
num_multinames)
tex_nMultiChip = latex_formater.latex_scalar(r'\# multichips',
num_multichips)
tex_multi_stats = latex_formater.latex_mystats(r'\# multistats',
multiton_nx2_nchips)
tex_kpts_scale_thresh = latex_formater.latex_multicolumn(
'Scale Threshold (%d %d)' %
(hs.prefs.feat_cfg.scale_min,
hs.prefs.feat_cfg.scale_max)) + r'\\' + '\n'
(tex_nKpts, tex_kpts_stats,
tex_scale_stats) = db_info.get_keypoint_stats(hs)
tex_title = latex_formater.latex_multicolumn(
db_name + ' database statistics') + r'\\' + '\n'
dedent = textwrap.dedent
tabular_head = dedent(r'''
\begin{tabular}{|l|l|}
''')
tabular_tail = dedent(r'''
\end{tabular}
''')
hline = ''.join([r'\hline', '\n'])
tabular_body_list = [
tex_title,
tex_nChip,
tex_nName,
tex_nSingleName,
tex_nMultiName,
tex_nMultiChip,
tex_multi_stats,
'',
tex_kpts_scale_thresh,
tex_nKpts,
tex_kpts_stats,
tex_scale_stats,
]
tabular_body = hline.join(tabular_body_list)
tabular = hline.join([tabular_head, tabular_body, tabular_tail])
print('[dev stats]')
print(tabular)
def dbstats(hs):
import db_info
# Chip / Name / Image stats
dbinfo_locals = db_info.db_info(hs)
db_name = hs.get_db_name(True)
#num_images = dbinfo_locals['num_images']
num_chips = dbinfo_locals['num_chips']
num_names = len(dbinfo_locals['valid_nxs'])
num_singlenames = len(dbinfo_locals['singleton_nxs'])
num_multinames = len(dbinfo_locals['multiton_nxs'])
num_multichips = len(dbinfo_locals['multiton_cxs'])
multiton_nx2_nchips = dbinfo_locals['multiton_nx2_nchips']
#tex_nImage = pytex.latex_scalar(r'\# images', num_images)
tex_nChip = pytex.latex_scalar(r'\# chips', num_chips)
tex_nName = pytex.latex_scalar(r'\# names', num_names)
tex_nSingleName = pytex.latex_scalar(r'\# singlenames', num_singlenames)
tex_nMultiName = pytex.latex_scalar(r'\# multinames', num_multinames)
tex_nMultiChip = pytex.latex_scalar(r'\# multichips', num_multichips)
tex_multi_stats = pytex.latex_mystats(r'\# multistats', multiton_nx2_nchips)
tex_kpts_scale_thresh = pytex.latex_multicolumn('Scale Threshold (%d %d)' %
(hs.prefs.feat_cfg.scale_min,
hs.prefs.feat_cfg.scale_max)) + r'\\' + '\n'
(tex_nKpts, tex_kpts_stats, tex_scale_stats) = db_info.get_keypoint_stats(hs)
tex_title = pytex.latex_multicolumn(db_name + ' database statistics') + r'\\' + '\n'
dedent = textwrap.dedent
tabular_head = dedent(r'''
\begin{tabular}{|l|l|}
''')
tabular_tail = dedent(r'''
\end{tabular}
''')
hline = ''.join([r'\hline', '\n'])
tabular_body_list = [
tex_title,
tex_nChip,
tex_nName,
tex_nSingleName,
tex_nMultiName,
tex_nMultiChip,
tex_multi_stats,
'',
tex_kpts_scale_thresh,
tex_nKpts,
tex_kpts_stats,
tex_scale_stats,
]
tabular_body = hline.join(tabular_body_list)
tabular = hline.join([tabular_head, tabular_body, tabular_tail])
print(tabular)
def get_keypoint_stats(hs):
from hscom import latex_formater as pytex
hs.dbg_cx2_kpts()
# Keypoint stats
cx2_kpts = hs.feats.cx2_kpts
# Check cx2_kpts
cx2_nFeats = map(len, cx2_kpts)
kpts = np.vstack(cx2_kpts)
print('[dbinfo] --- LaTeX --- ')
_printopts = np.get_printoptions()
np.set_printoptions(precision=3)
acd = kpts[:, 2:5].T
scales = np.sqrt(acd[0] * acd[2])
scales = np.array(sorted(scales))
tex_scale_stats = pytex.latex_mystats(r'kpt scale', scales)
tex_nKpts = pytex.latex_scalar(r'\# kpts', len(kpts))
tex_kpts_stats = pytex.latex_mystats(r'\# kpts/chip', cx2_nFeats)
print(tex_nKpts)
print(tex_kpts_stats)
print(tex_scale_stats)
np.set_printoptions(**_printopts)
print('[dbinfo] ---/LaTeX --- ')
return (tex_nKpts, tex_kpts_stats, tex_scale_stats)
