def vary_two_cfg(hs, qcx, cx, query_cfg, vary_cfg, fnum=1):
if len(vary_cfg) > 2:
raise Exception('can only vary at most two cfgeters')
print('[dev] vary_two_cfg: q' + hs.vs_str(qcx, cx))
cfg_keys = vary_cfg.keys()
cfg_vals = vary_cfg.values()
cfg1_name = cfg_keys[0]
cfg2_name = cfg_keys[1]
cfg1_steps = cfg_vals[0]
cfg2_steps = cfg_vals[1]
nRows = len(cfg1_steps)
nCols = len(cfg2_steps)
print('[dev] Varying configs: nRows=%r, nCols=%r' % (nRows, nCols))
print('[dev] %r = %r ' % (cfg1_name, cfg1_steps))
print('[dev] %r = %r ' % (cfg2_name, cfg2_steps))
ylabel_args = dict(rotation='horizontal',
verticalalignment='bottom',
horizontalalignment='right',
fontproperties=df2.FONTS.medbold)
xlabel_args = dict(fontproperties=df2.FONTS.medbold)
#ax = df2.gca()
# Vary cfg1
#df2..gcf().clf()
print_lock_ = helpers.ModulePrintLock(mc3, df2)
assign_alg = query_cfg.agg_cfg.query_type
vert = not hs.args.horiz
plt_match_args = dict(fnum=fnum, show_gname=False, showTF=False, vert=vert)
for rowx, cfg1_value in enumerate(cfg1_steps):
query_cfg.update_cfg(**{cfg1_name: cfg1_value})
y_title = cfg1_name + '=' + helpers.format(cfg1_value, 3)
# Vary cfg2
for colx, cfg2_value in enumerate(cfg2_steps):
query_cfg.update_cfg(**{cfg2_name: cfg2_value})
pnum = (nRows, nCols, rowx * nCols + colx + 1)
# HACK
#print(pnum)
#print(query_cfg)
# query only the chips of interest (groundtruth) when doing vsone
if assign_alg == 'vsone':
res = hs.query_groundtruth(qcx, query_cfg)
# query the entire database in vsmany (just as fast as vgroundtruth)
elif assign_alg == 'vsmany':
res = hs.query(qcx, query_cfg)
res.plot_single_match(hs, cx, pnum=pnum, **plt_match_args)
x_title = cfg2_name + '=' + helpers.format(cfg2_value, 3) # helpers.commas(cfg2_value, 3)
ax = df2.gca()
if rowx == len(cfg1_steps) - 1:
ax.set_xlabel(x_title, **xlabel_args)
if colx == 0:
ax.set_ylabel(y_title, **ylabel_args)
del print_lock_
vary_title = '%s vary %s and %s' % (assign_alg, cfg1_name, cfg2_name)
figtitle = '%s %s %s' % (vary_title, hs.vs_str(qcx, cx), str(hs.cx2_property(qcx, 'Notes')))
subtitle = mc3.simplify_test_uid(query_cfg.get_uid())
df2.set_figtitle(figtitle, subtitle)
df2.adjust_subplots_xylabels()
fnum += 1
viz.save_if_requested(hs, vary_title)
return fnum
def viz_chipgraph(hs, graph, fnum=1, with_images=False):
# Adapated from
# https://gist.github.com/shobhit/3236373
print('[encounter] drawing chip graph')
df2.figure(fnum=fnum, pnum=(1, 1, 1))
ax = df2.gca()
#pos = netx.spring_layout(graph)
pos = netx.graphviz_layout(graph)
netx.draw(graph, pos=pos, ax=ax)
if with_images:
cx_list = graph.nodes()
pos_list = [pos[cx] for cx in cx_list]
thumb_list = hs.get_thumb(cx_list, 16, 16)
draw_images_at_positions(thumb_list, pos_list)
def draw_images_at_positions(img_list, pos_list):
print('[encounter] drawing %d images' % len(img_list))
# Thumb stack
ax = df2.gca()
fig = df2.gcf()
trans = ax.transData.transform
trans2 = fig.transFigure.inverted().transform
mark_progress, end_progress = util.progress_func(len(pos_list), lbl='drawing img')
for ix, ((x, y), img) in enumerate(izip(pos_list, img_list)):
mark_progress(ix)
xx, yy = trans((x, y)) # figure coordinates
xa, ya = trans2((xx, yy)) # axes coordinates
#
width, height = img.shape[0:2]
tlx = xa - (width / 2.0)
tly = ya - (height / 2.0)
img_bbox = [tlx, tly, width, height]
# Make new axis for the image
img_ax = df2.plt.axes(img_bbox)
img_ax.imshow(img)
img_ax.set_aspect('equal')
img_ax.axis('off')
end_progress()
def vary_two_cfg(hs, qcx, cx, query_cfg, vary_cfg, fnum=1):
if len(vary_cfg) > 2:
raise Exception('can only vary at most two cfgeters')
print('[dev] vary_two_cfg: q' + hs.vs_str(qcx, cx))
cfg_keys = vary_cfg.keys()
cfg_vals = vary_cfg.values()
cfg1_name = cfg_keys[0]
cfg2_name = cfg_keys[1]
cfg1_steps = cfg_vals[0]
cfg2_steps = cfg_vals[1]
nRows = len(cfg1_steps)
nCols = len(cfg2_steps)
print('[dev] Varying configs: nRows=%r, nCols=%r' % (nRows, nCols))
print('[dev] %r = %r ' % (cfg1_name, cfg1_steps))
print('[dev] %r = %r ' % (cfg2_name, cfg2_steps))
ylabel_args = dict(rotation='horizontal',
verticalalignment='bottom',
horizontalalignment='right',
fontproperties=df2.FONTS.medbold)
xlabel_args = dict(fontproperties=df2.FONTS.medbold)
#ax = df2.gca()
# Vary cfg1
#df2..gcf().clf()
print_lock_ = helpers.ModulePrintLock(mc3, df2)
assign_alg = query_cfg.agg_cfg.query_type
vert = not hs.args.horiz
plt_match_args = dict(fnum=fnum, show_gname=False, showTF=False, vert=vert)
for rowx, cfg1_value in enumerate(cfg1_steps):
query_cfg.update_cfg(**{cfg1_name: cfg1_value})
y_title = cfg1_name + '=' + helpers.format(cfg1_value, 3)
# Vary cfg2
for colx, cfg2_value in enumerate(cfg2_steps):
query_cfg.update_cfg(**{cfg2_name: cfg2_value})
pnum = (nRows, nCols, rowx * nCols + colx + 1)
# HACK
#print(pnum)
#print(query_cfg)
# query only the chips of interest (groundtruth) when doing vsone
if assign_alg == 'vsone':
res = hs.query_groundtruth(qcx, query_cfg)
# query the entire database in vsmany (just as fast as vgroundtruth)
elif assign_alg == 'vsmany':
res = hs.query(qcx, query_cfg)
res.plot_single_match(hs, cx, pnum=pnum, **plt_match_args)
x_title = cfg2_name + '=' + helpers.format(
cfg2_value, 3) # helpers.commas(cfg2_value, 3)
ax = df2.gca()
if rowx == len(cfg1_steps) - 1:
ax.set_xlabel(x_title, **xlabel_args)
if colx == 0:
ax.set_ylabel(y_title, **ylabel_args)
del print_lock_
vary_title = '%s vary %s and %s' % (assign_alg, cfg1_name, cfg2_name)
figtitle = '%s %s %s' % (vary_title, hs.vs_str(
qcx, cx), str(hs.cx2_property(qcx, 'Notes')))
subtitle = mc3.simplify_test_uid(query_cfg.get_uid())
df2.set_figtitle(figtitle, subtitle)
df2.adjust_subplots_xylabels()
fnum += 1
viz.save_if_requested(hs, vary_title)
return fnum
def annotate_chipres(hs, res, cx, showTF=True, showScore=True, title_pref='',
title_suff='', show_2nd_gname=True, show_2nd_name=True,
show_1st=True,
time_appart=True, in_image=False, offset1=(0, 0),
offset2=(0, 0), show_query=True, xywh2=None, **kwargs):
printDBG('[viz] annotate_chipres()')
#print('Did not expect args: %r' % (kwargs.keys(),))
qcx = res.qcx
score = res.cx2_score[cx]
matched_kpts= np.float32(len(res.cx2_fs[cx]))
print('matched_kpts=%d'%matched_kpts)
# TODO Use this function when you clean show_chipres
(truestr, falsestr, nonamestr) = ('TRUE', 'FALSE', '???')
is_true, is_unknown = hs.is_true_match(qcx, cx)
isgt_str = nonamestr if is_unknown else (truestr if is_true else falsestr)
match_color = {nonamestr: df2.UNKNOWN_PURP,
truestr: df2.TRUE_GREEN,
falsestr: df2.FALSE_RED}[isgt_str]
# Build title
title = '*%s*' % isgt_str if showTF else ''
if showScore:
score_str = (' score=' + helpers.num_fmt(score))% (score)
score_str +=(' matched_kpts='+ helpers.num_fmt(matched_kpts))% (matched_kpts)
title += score_str
title = title_pref + str(title) + title_suff
# Build xlabel
xlabel_ = []
ax = df2.gca()
ax._hs_viewtype = 'chipres'
ax._hs_qcx = qcx
ax._hs_cx = cx
if 'show_1st':
xlabel_.append('top_gname=%r'%hs.cx2_gname(qcx))
xlabel_.append('top_name=%r'%hs.cx2_name(qcx))
if 'show_2nd_gname':
xlabel_.append('\n below_gname=%r' % hs.cx2_gname(cx))
if 'show_2nd_name':
xlabel_.append('below_name=%r' % hs.cx2_name(cx))
if 'time_appart':
xlabel_.append('\n' + hs.get_timedelta_str(qcx, cx))
xlabel = ', '.join(xlabel_)
if NO_LABEL_OVERRIDE:
title = ''
xlabel = ''
df2.set_title(title, ax)
df2.set_xlabel(xlabel, ax)
if in_image:
roi1 = hs.cx2_roi(qcx) + np.array(list(offset1) + [0, 0])
roi2 = hs.cx2_roi(cx) + np.array(list(offset2) + [0, 0])
theta1 = hs.cx2_theta(qcx)
theta2 = hs.cx2_theta(cx)
# HACK!
lbl1 = 'q' + hs.cidstr(qcx)
lbl2 = hs.cidstr(cx)
if show_query:
df2.draw_roi(roi1, bbox_color=df2.ORANGE, label=lbl1, theta=theta1)
df2.draw_roi(roi2, bbox_color=match_color, label=lbl2, theta=theta2)
# No matches draw a red box
if len(res.cx2_fm[cx]) == 0:
df2.draw_boxedX(roi2, theta=theta2)
else:
if xywh2 is None:
xy, w, h = df2._axis_xy_width_height(ax)
xywh2 = (xy[0], xy[1], w, h)
df2.draw_border(ax, match_color, 4, offset=offset2)
# No matches draw a red box
if len(res.cx2_fm[cx]) == 0:
df2.draw_boxedX(xywh2)