def _draw_matches(title, fm, px):
# Helper with common arguments to df2.show_chipmatch2
dmkwargs = dict(fs=None,
title=title,
all_kpts=False,
draw_lines=True,
docla=True,
fnum=fnum,
pnum=(3, 3, px))
df2.show_chipmatch2(rchip1,
rchip2,
kpts1,
kpts2,
fm,
show_nMatches=True,
**dmkwargs)
def show_chipres(hs, res, cx, fnum=None, pnum=None, sel_fm=[], in_image=False, **kwargs):
'shows single annotated match result.'
qcx = res.qcx
#cx2_score = res.get_cx2_score()
cx2_fm = res.get_cx2_fm()
cx2_fs = res.get_cx2_fs()
#cx2_fk = res.get_cx2_fk()
#printDBG('[viz.show_chipres()] Showing matches from %s' % (vs_str))
#printDBG('[viz.show_chipres()] fnum=%r, pnum=%r' % (fnum, pnum))
# Test valid cx
printDBG('[viz] show_chipres()')
if np.isnan(cx):
nan_img = np.zeros((32, 32), dtype=np.uint8)
title = '(q%s v %r)' % (hs.cidstr(qcx), cx)
df2.imshow(nan_img, fnum=fnum, pnum=pnum, title=title)
return
fm = cx2_fm[cx]
fs = cx2_fs[cx]
#fk = cx2_fk[cx]
#vs_str = hs.vs_str(qcx, cx)
# Read query and result info (chips, names, ...)
if in_image:
# TODO: rectify build_transform2 with cc2
# clean up so its not abysmal
rchip1, rchip2 = [hs.cx2_image(_) for _ in [qcx, cx]]
kpts1, kpts2 = cx2_imgkpts(hs, [qcx, cx])
else:
rchip1, rchip2 = hs.get_chip([qcx, cx])
kpts1, kpts2 = hs.get_kpts([qcx, cx])
# Build annotation strings / colors
lbl1 = 'q' + hs.cidstr(qcx)
lbl2 = hs.cidstr(cx)
if in_image:
# HACK!
lbl1 = None
lbl2 = None
# Draws the chips and keypoint matches
kwargs_ = dict(fs=fs, lbl1=lbl1, lbl2=lbl2, fnum=fnum,
pnum=pnum, vert=hs.prefs.display_cfg.vert)
kwargs_.update(kwargs)
ax, xywh1, xywh2 = df2.show_chipmatch2(rchip1, rchip2, kpts1, kpts2, fm, **kwargs_)
x1, y1, w1, h1 = xywh1
x2, y2, w2, h2 = xywh2
if len(sel_fm) > 0:
# Draw any selected matches
_smargs = dict(rect=True, colors=df2.BLUE)
df2.draw_fmatch(xywh1, xywh2, kpts1, kpts2, sel_fm, **_smargs)
offset1 = (x1, y1)
offset2 = (x2, y2)
annotate_chipres(hs, res, cx, xywh2=xywh2, in_image=in_image, offset1=offset1, offset2=offset2, **kwargs)
return ax, xywh1, xywh2
def show_chipres(hs,
res,
cx,
fnum=None,
pnum=None,
sel_fm=[],
in_image=False,
**kwargs):
'shows single annotated match result.'
qcx = res.qcx
#cx2_score = res.get_cx2_score()
cx2_fm = res.get_cx2_fm()
cx2_fs = res.get_cx2_fs()
#cx2_fk = res.get_cx2_fk()
#printDBG('[viz.show_chipres()] Showing matches from %s' % (vs_str))
#printDBG('[viz.show_chipres()] fnum=%r, pnum=%r' % (fnum, pnum))
# Test valid cx
printDBG('[viz] show_chipres()')
if np.isnan(cx):
nan_img = np.zeros((32, 32), dtype=np.uint8)
title = '(q%s v %r)' % (hs.cidstr(qcx), cx)
df2.imshow(nan_img, fnum=fnum, pnum=pnum, title=title)
return
fm = cx2_fm[cx]
fs = cx2_fs[cx]
#fk = cx2_fk[cx]
#vs_str = hs.vs_str(qcx, cx)
# Read query and result info (chips, names, ...)
if in_image:
# TODO: rectify build_transform2 with cc2
# clean up so its not abysmal
rchip1, rchip2 = [hs.cx2_image(_) for _ in [qcx, cx]]
kpts1, kpts2 = cx2_imgkpts(hs, [qcx, cx])
else:
rchip1, rchip2 = hs.get_chip([qcx, cx])
kpts1, kpts2 = hs.get_kpts([qcx, cx])
# Build annotation strings / colors
lbl1 = 'q' + hs.cidstr(qcx)
lbl2 = hs.cidstr(cx)
if in_image:
# HACK!
lbl1 = None
lbl2 = None
# Draws the chips and keypoint matches
kwargs_ = dict(fs=fs,
lbl1=lbl1,
lbl2=lbl2,
fnum=fnum,
pnum=pnum,
vert=hs.prefs.display_cfg.vert)
kwargs_.update(kwargs)
ax, xywh1, xywh2 = df2.show_chipmatch2(rchip1, rchip2, kpts1, kpts2, fm,
**kwargs_)
x1, y1, w1, h1 = xywh1
x2, y2, w2, h2 = xywh2
if len(sel_fm) > 0:
# Draw any selected matches
_smargs = dict(rect=True, colors=df2.BLUE)
df2.draw_fmatch(xywh1, xywh2, kpts1, kpts2, sel_fm, **_smargs)
offset1 = (x1, y1)
offset2 = (x2, y2)
annotate_chipres(hs,
res,
cx,
xywh2=xywh2,
in_image=in_image,
offset1=offset1,
offset2=offset2,
**kwargs)
return ax, xywh1, xywh2
def _draw_matches(title, fm, px):
# Helper with common arguments to df2.show_chipmatch2
dmkwargs = dict(fs=None, title=title, all_kpts=False, draw_lines=True,
docla=True, fnum=fnum, pnum=(3, 3, px))
df2.show_chipmatch2(rchip1, rchip2, kpts1, kpts2, fm, show_nMatches=True, **dmkwargs)
