def test_shape(ori=0, skew=0, xscale=1, yscale=1, pnum=(1, 1, 1), fnum=1):
df2.figure(fnum=fnum, pnum=pnum)
kpts, sifts = test_keypoint(ori=ori,
skew=skew,
xscale=xscale,
yscale=yscale)
ax = df2.gca()
square_axis(ax)
mpl_keypoint.draw_keypoints(ax,
kpts,
sifts=sifts,
ell_color=df2.ORANGE,
ori=True,
rect_color=df2.DARK_RED,
ori_color=df2.DEEP_PINK,
eig_color=df2.PINK,
rect=True,
eig=True,
bin_color=df2.RED,
arm1_color=df2.YELLOW,
arm2_color=df2.BLACK)
kptsstr = '\n'.join(ktool.get_kpts_strs(kpts))
#print(kptsstr)
df2.upperleft_text(kptsstr)
title = 'xyscale=(%.1f, %.1f),\n skew=%.1f, ori=%.2ftau' % (
xscale, yscale, skew, ori / TAU)
df2.set_title(title)
df2.dark_background()
return kpts, sifts
def annotate_matches(ibs, qres, aid2,
offset1=(0, 0),
offset2=(0, 0),
xywh2=(0, 0, 0, 0),
xywh1=(0, 0, 0, 0),
**kwargs):
# TODO Use this function when you clean show_matches
in_image = kwargs.get('in_image', False)
show_query = kwargs.get('show_query', True)
draw_border = kwargs.get('draw_border', True)
draw_lbl = kwargs.get('draw_lbl', True)
printDBG('[viz] annotate_matches()')
aid1 = qres.qaid
truth = ibs.get_match_truth(aid1, aid2)
truth_color = vh.get_truth_color(truth)
# Build title
title = vh.get_query_text(ibs, qres, aid2, truth, **kwargs)
# Build xlbl
ax = df2.gca()
ph.set_plotdat(ax, 'viztype', 'matches')
ph.set_plotdat(ax, 'qaid', aid1)
ph.set_plotdat(ax, 'aid1', aid1)
ph.set_plotdat(ax, 'aid2', aid2)
if draw_lbl:
name1, name2 = ibs.get_annot_names([aid1, aid2])
lbl1 = repr(name1) + ' : ' + 'q' + vh.get_aidstrs(aid1)
lbl2 = repr(name2) + ' : ' + vh.get_aidstrs(aid2)
else:
lbl1, lbl2 = None, None
if vh.NO_LBL_OVERRIDE:
title = ''
df2.set_title(title, ax)
# Plot annotations over images
if in_image:
bbox1, bbox2 = vh.get_bboxes(ibs, [aid1, aid2], [offset1, offset2])
theta1, theta2 = ibs.get_annot_thetas([aid1, aid2])
# HACK!
if show_query:
df2.draw_bbox(bbox1, bbox_color=df2.ORANGE, lbl=lbl1, theta=theta1)
bbox_color2 = truth_color if draw_border else df2.ORANGE
df2.draw_bbox(bbox2, bbox_color=bbox_color2, lbl=lbl2, theta=theta2)
else:
xy, w, h = df2._axis_xy_width_height(ax)
bbox2 = (xy[0], xy[1], w, h)
theta2 = 0
if draw_border:
df2.draw_border(ax, truth_color, 4, offset=offset2)
if draw_lbl:
# Custom user lbl for chips 1 and 2
(x1, y1, w1, h1) = xywh1
(x2, y2, w2, h2) = xywh2
df2.absolute_lbl(x1 + w1, y1, lbl1)
df2.absolute_lbl(x2 + w2, y2, lbl2)
# No matches draw a red box
if aid2 not in qres.aid2_fm or len(qres.aid2_fm[aid2]) == 0:
if draw_border:
df2.draw_boxedX(bbox2, theta=theta2)
def show_keypoint_gradient_orientations(ibs, aid, fx, fnum=None, pnum=None, config2_=None):
# Draw the gradient vectors of a patch overlaying the keypoint
if fnum is None:
fnum = df2.next_fnum()
rchip = ibs.get_annot_chips(aid, config2_=config2_)
kp = ibs.get_annot_kpts(aid, config2_=config2_)[fx]
sift = ibs.get_annot_vecs(aid, config2_=config2_)[fx]
df2.draw_keypoint_gradient_orientations(rchip, kp, sift=sift,
mode='vec', fnum=fnum, pnum=pnum)
df2.set_title('Gradient orientation\n %s, fx=%d' % (get_aidstrs(aid), fx))
def test_shape(ori=0, skew=0, xscale=1, yscale=1, pnum=(1, 1, 1), fnum=1):
df2.figure(fnum=fnum, pnum=pnum)
kpts, sifts = test_keypoint(ori=ori, skew=skew, xscale=xscale, yscale=yscale)
ax = df2.gca()
square_axis(ax)
mpl_keypoint.draw_keypoints(ax, kpts, sifts=sifts, ell_color=df2.ORANGE, ori=True,
rect_color=df2.DARK_RED,
ori_color=df2.DEEP_PINK, eig_color=df2.PINK,
rect=True, eig=True, bin_color=df2.RED,
arm1_color=df2.YELLOW, arm2_color=df2.BLACK)
kptsstr = '\n'.join(ktool.get_kpts_strs(kpts))
#print(kptsstr)
df2.upperleft_text(kptsstr)
title = 'xyscale=(%.1f, %.1f),\n skew=%.1f, ori=%.2ftau' % (xscale, yscale, skew, ori / TAU)
df2.set_title(title)
df2.dark_background()
return kpts, sifts
def show_keypoint_gradient_orientations(ibs,
aid,
fx,
fnum=None,
pnum=None,
config2_=None):
# Draw the gradient vectors of a patch overlaying the keypoint
if fnum is None:
fnum = df2.next_fnum()
rchip = ibs.get_annot_chips(aid, config2_=config2_)
kp = ibs.get_annot_kpts(aid, config2_=config2_)[fx]
sift = ibs.get_annot_vecs(aid, config2_=config2_)[fx]
df2.draw_keypoint_gradient_orientations(rchip,
kp,
sift=sift,
mode='vec',
fnum=fnum,
pnum=pnum)
df2.set_title('Gradient orientation\n %s, fx=%d' % (get_aidstrs(aid), fx))
def TEST_figure1(wpatch, gradx, grady, gmag, gori, hist, centers):
from plottool import draw_func2 as df2
import plottool
import vtool.patch as ptool
print('[rotinvar] 4) Draw histogram with interpolation annotations')
fnum = 1
gorimag = plottool.color_orimag(gori, gmag, True)
nRow, nCol = (2, 7)
df2.figure(fnum=1, pnum=(nRow, 1, nRow), doclf=True, docla=True)
plottool.draw_hist_subbin_maxima(hist, centers)
df2.set_xlabel('grad orientation (radians)')
df2.set_ylabel('grad magnitude')
df2.set_title('dominant orientations')
print('[rotinvar] 5) Show patch, gradients, magintude, and orientation')
df2.imshow(wpatch, pnum=(nRow, nCol, 1), fnum=fnum, title='patch')
df2.draw_vector_field(gradx,
grady,
pnum=(nRow, nCol, 2),
fnum=fnum,
title='gori (vec)')
df2.imshow(gorimag, pnum=(nRow, nCol, 3), fnum=fnum, title='gori (col)')
df2.imshow(np.abs(gradx), pnum=(nRow, nCol, 4), fnum=fnum, title='gradx')
df2.imshow(np.abs(grady), pnum=(nRow, nCol, 5), fnum=fnum, title='grady')
df2.imshow(gmag, pnum=(nRow, nCol, 6), fnum=fnum, title='gmag')
gpatch = ptool.gaussian_patch(shape=gori.shape)
df2.imshow(gpatch * 255,
pnum=(nRow, nCol, 7),
fnum=fnum,
title='gauss weights',
cmap_='hot')
#gpatch3 = np.dstack((gpatch, gpatch, gpatch))
#df2.draw_vector_field(gradx * gpatch, grady * gpatch, pnum=(nRow, nCol, 8), fnum=fnum, title='gori (vec)')
#df2.imshow(gorimag * gpatch3, pnum=(nRow, nCol, 9), fnum=fnum, title='gori (col)')
#df2.imshow(gradx * gpatch, pnum=(nRow, nCol, 10), fnum=fnum, title='gradx')
#df2.imshow(grady * gpatch, pnum=(nRow, nCol, 11), fnum=fnum, title='grady')
#df2.imshow(gmag * gpatch, pnum=(nRow, nCol, 12), fnum=fnum, title='gmag')
return locals()
