def _on_chip_click(event):
print_('[inter] clicked chip')
ax, x, y = event.inaxes, event.xdata, event.ydata
if ax is None or x is None:
# The click is not in any axis
print('... out of axis')
annote_ptr[0] = (annote_ptr[0] + 1) % 3
mode = annote_ptr[0]
draw_ell = mode == 1
draw_pts = mode == 2
print('... default kpts view mode=%r' % mode)
_chip_view(draw_ell=draw_ell, draw_pts=draw_pts)
else:
hs_viewtype = ax.__dict__.get('_hs_viewtype', '')
print_(' hs_viewtype=%r' % hs_viewtype)
if hs_viewtype == 'chip' and event.key == 'shift':
print('... masking')
# TODO: Do better integration of masking
_chip_view()
df2.disconnect_callback(fig, 'button_press_event')
mc = mask_creator.MaskCreator(df2.gca()) # NOQA
elif hs_viewtype == 'chip':
kpts = hs.get_kpts(cx)
if len(kpts) > 0:
fx = nearest_point(x, y, kpts)[0]
print('... clicked fx=%r' % fx)
_select_ith_kpt(fx)
else:
print('... len(kpts) == 0')
else:
print('...Unknown viewtype')
viz.draw()
def _ctrlclicked_cx(cx):
printDBG('ctrl+clicked cx=%r' % cx)
fnum = FNUMS['special']
fig = df2.figure(fnum=fnum, docla=True, doclf=True)
df2.disconnect_callback(fig, 'button_press_event')
viz_spatial_verification(hs, res.qcx, cx2=cx, fnum=fnum)
fig.canvas.draw()
df2.bring_to_front(fig)
def _ctrlclicked_cx(cx):
printDBG('ctrl+clicked cx=%r' % cx)
fnum = FNUMS['special']
fig = df2.figure(fnum=fnum, docla=True, doclf=True)
df2.disconnect_callback(fig, 'button_press_event')
viz_spatial_verification(hs, res.qcx, cx2=cx, fnum=fnum)
fig.canvas.draw()
df2.bring_to_front(fig)
def _show_res(hs, res, **kwargs):
''' Displays query chip, groundtruth matches, and top 5 matches'''
#printDBG('[viz._show_res()] %s ' % helpers.printableVal(locals()))
#printDBG = print
in_image = hs.prefs.display_cfg.show_results_in_image
annote = kwargs.pop('annote', 2) # this is toggled
fnum = kwargs.get('fnum', 3)
figtitle = kwargs.get('figtitle', '')
topN_cxs = kwargs.get('topN_cxs', [])
gt_cxs = kwargs.get('gt_cxs', [])
all_kpts = kwargs.get('all_kpts', False)
interact = kwargs.get('interact', True)
show_query = kwargs.get('show_query', False)
dosquare = kwargs.get('dosquare', False)
if SHOW_QUERY_OVERRIDE is not None:
show_query = SHOW_QUERY_OVERRIDE
max_nCols = 5
if len(topN_cxs) in [6, 7]:
max_nCols = 3
if len(topN_cxs) in [8]:
max_nCols = 4
printDBG('========================')
printDBG('[viz._show_res()]----------------')
all_gts = hs.get_other_indexed_cxs(res.qcx)
_tup = tuple(map(len, (topN_cxs, gt_cxs, all_gts)))
printDBG('[viz._show_res()] #topN=%r #missed_gts=%r/%r' % _tup)
printDBG('[viz._show_res()] * fnum=%r' % (fnum, ))
printDBG('[viz._show_res()] * figtitle=%r' % (figtitle, ))
printDBG('[viz._show_res()] * max_nCols=%r' % (max_nCols, ))
printDBG('[viz._show_res()] * show_query=%r' % (show_query, ))
ranked_cxs = res.topN_cxs(hs, N='all')
# Build a subplot grid
nQuerySubplts = 1 if show_query else 0
nGtSubplts = nQuerySubplts + (0 if gt_cxs is None else len(gt_cxs))
nTopNSubplts = 0 if topN_cxs is None else len(topN_cxs)
nTopNCols = min(max_nCols, nTopNSubplts)
nGTCols = min(max_nCols, nGtSubplts)
nGTCols = max(nGTCols, nTopNCols)
nTopNCols = nGTCols
nGtRows = 0 if nGTCols == 0 else int(np.ceil(nGtSubplts / nGTCols))
nTopNRows = 0 if nTopNCols == 0 else int(np.ceil(nTopNSubplts / nTopNCols))
nGtCells = nGtRows * nGTCols
nRows = nTopNRows + nGtRows
# HACK:
_color_list = df2.distinct_colors(len(topN_cxs))
cx2_color = {cx: _color_list[ox] for ox, cx in enumerate(topN_cxs)}
if IN_IMAGE_OVERRIDE is not None:
in_image = IN_IMAGE_OVERRIDE
# Helpers
def _show_query_fn(plotx_shift, rowcols):
'helper for viz._show_res'
plotx = plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
#print('[viz] Plotting Query: pnum=%r' % (pnum,))
_kwshow = dict(draw_kpts=annote)
_kwshow.update(kwargs)
_kwshow['prefix'] = 'q'
_kwshow['res'] = res
_kwshow['pnum'] = pnum
_kwshow['cx2_color'] = cx2_color
_kwshow['draw_ell'] = annote >= 1
#_kwshow['in_image'] = in_image
show_chip(hs, **_kwshow)
#if in_image:
#roi1 = hs.cx2_roi(res.qcx)
#df2.draw_roi(roi1, bbox_color=df2.ORANGE, label='q' + hs.cidstr(res.qcx))
def _plot_matches_cxs(cx_list, plotx_shift, rowcols):
def _show_matches_fn(cx, orank, pnum):
'Helper function for drawing matches to one cx'
aug = 'rank=%r\n' % orank
#printDBG('[viz._show_res()] plotting: %r' % (pnum,))
_kwshow = dict(draw_ell=annote,
draw_pts=False,
draw_lines=annote,
ell_alpha=.5,
all_kpts=all_kpts)
_kwshow.update(kwargs)
_kwshow['fnum'] = fnum
_kwshow['pnum'] = pnum
_kwshow['title_aug'] = aug
# If we already are showing the query dont show it here
if not show_query:
_kwshow['draw_ell'] = annote == 1
_kwshow['draw_lines'] = annote >= 1
res_show_chipres(res, hs, cx, in_image=in_image, **_kwshow)
else:
_kwshow['draw_ell'] = annote >= 1
if annote == 2:
# TODO Find a better name
_kwshow['color'] = cx2_color[cx]
_kwshow['sel_fx2'] = res.cx2_fm[cx][:, 1]
show_chip(hs, cx, in_image=in_image, **_kwshow)
annotate_chipres(hs,
res,
cx,
in_image=in_image,
show_query=not show_query)
'helper for viz._show_res to draw many cxs'
#printDBG('[viz._show_res()] Plotting Chips %s:' % hs.cidstr(cx_list))
if cx_list is None:
return
for ox, cx in enumerate(cx_list):
plotx = ox + plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
oranks = np.where(ranked_cxs == cx)[0]
if len(oranks) == 0:
orank = -1
continue
orank = oranks[0] + 1
_show_matches_fn(cx, orank, pnum)
if dosquare:
# HACK
nSubplots = nGtSubplts + nTopNSubplts
nRows, nCols = get_square_row_cols(nSubplots, 3)
nTopNCols = nGTCols = nCols
shift_topN = 1
printDBG('nRows, nCols = (%r, %r)' % (nRows, nCols))
else:
shift_topN = nGtCells
if nGtSubplts == 1:
nGTCols = 1
fig = df2.figure(fnum=fnum,
pnum=(nRows, nGTCols, 1),
docla=True,
doclf=True)
df2.disconnect_callback(fig, 'button_press_event')
df2.plt.subplot(nRows, nGTCols, 1)
# Plot Query
if show_query:
_show_query_fn(0, (nRows, nGTCols))
# Plot Ground Truth
_plot_matches_cxs(gt_cxs, nQuerySubplts, (nRows, nGTCols))
_plot_matches_cxs(topN_cxs, shift_topN, (nRows, nTopNCols))
figtitle += ' q%s name=%s' % (hs.cidstr(res.qcx), hs.cx2_name(res.qcx))
df2.set_figtitle(figtitle, incanvas=not NO_LABEL_OVERRIDE)
# Result Interaction
if interact:
printDBG('[viz._show_res()] starting interaction')
def _ctrlclicked_cx(cx):
printDBG('ctrl+clicked cx=%r' % cx)
fnum = FNUMS['special']
fig = df2.figure(fnum=fnum, docla=True, doclf=True)
df2.disconnect_callback(fig, 'button_press_event')
viz_spatial_verification(hs, res.qcx, cx2=cx, fnum=fnum)
fig.canvas.draw()
df2.bring_to_front(fig)
def _clicked_cx(cx):
printDBG('clicked cx=%r' % cx)
fnum = FNUMS['inspect']
res.interact_chipres(hs, cx, fnum=fnum)
fig = df2.gcf()
fig.canvas.draw()
df2.bring_to_front(fig)
def _clicked_none():
# Toggle if the click is not in any axis
printDBG('clicked none')
#print(kwargs)
_show_res(hs, res, annote=(annote + 1) % 3, **kwargs)
fig.canvas.draw()
def _on_res_click(event):
'result interaction mpl event callback slot'
print('[viz] clicked result')
if event.xdata is None or event.inaxes is None:
#print('clicked outside axes')
return _clicked_none()
ax = event.inaxes
hs_viewtype = ax.__dict__.get('_hs_viewtype', '')
printDBG(event.__dict__)
printDBG('hs_viewtype=%r' % hs_viewtype)
# Clicked a specific chipres
if hs_viewtype.find('chipres') == 0:
cx = ax.__dict__.get('_hs_cx')
# Ctrl-Click
key = '' if event.key is None else event.key
print('key = %r' % key)
if key.find('control') == 0:
print('[viz] result control clicked')
return _ctrlclicked_cx(cx)
# Left-Click
else:
print('[viz] result clicked')
return _clicked_cx(cx)
df2.connect_callback(fig, 'button_press_event', _on_res_click)
df2.adjust_subplots_safe()
printDBG('[viz._show_res()] Finished')
return fig
def _show_res(hs, res, **kwargs):
''' Displays query chip, groundtruth matches, and top 5 matches'''
#printDBG('[viz._show_res()] %s ' % helpers.printableVal(locals()))
#printDBG = print
in_image = hs.prefs.display_cfg.show_results_in_image
annote = kwargs.pop('annote', 2) # this is toggled
fnum = kwargs.get('fnum', 3)
figtitle = kwargs.get('figtitle', '')
topN_cxs = kwargs.get('topN_cxs', [])
gt_cxs = kwargs.get('gt_cxs', [])
all_kpts = kwargs.get('all_kpts', False)
interact = kwargs.get('interact', True)
show_query = kwargs.get('show_query', False)
dosquare = kwargs.get('dosquare', False)
if SHOW_QUERY_OVERRIDE is not None:
show_query = SHOW_QUERY_OVERRIDE
max_nCols = 5
if len(topN_cxs) in [6, 7]:
max_nCols = 3
if len(topN_cxs) in [8]:
max_nCols = 4
printDBG('========================')
printDBG('[viz._show_res()]----------------')
all_gts = hs.get_other_indexed_cxs(res.qcx)
_tup = tuple(map(len, (topN_cxs, gt_cxs, all_gts)))
printDBG('[viz._show_res()] #topN=%r #missed_gts=%r/%r' % _tup)
printDBG('[viz._show_res()] * fnum=%r' % (fnum,))
printDBG('[viz._show_res()] * figtitle=%r' % (figtitle,))
printDBG('[viz._show_res()] * max_nCols=%r' % (max_nCols,))
printDBG('[viz._show_res()] * show_query=%r' % (show_query,))
ranked_cxs = res.topN_cxs(hs, N='all')
# Build a subplot grid
nQuerySubplts = 1 if show_query else 0
nGtSubplts = nQuerySubplts + (0 if gt_cxs is None else len(gt_cxs))
nTopNSubplts = 0 if topN_cxs is None else len(topN_cxs)
nTopNCols = min(max_nCols, nTopNSubplts)
nGTCols = min(max_nCols, nGtSubplts)
nGTCols = max(nGTCols, nTopNCols)
nTopNCols = nGTCols
nGtRows = 0 if nGTCols == 0 else int(np.ceil(nGtSubplts / nGTCols))
nTopNRows = 0 if nTopNCols == 0 else int(np.ceil(nTopNSubplts / nTopNCols))
nGtCells = nGtRows * nGTCols
nRows = nTopNRows + nGtRows
# HACK:
_color_list = df2.distinct_colors(len(topN_cxs))
cx2_color = {cx: _color_list[ox] for ox, cx in enumerate(topN_cxs)}
if IN_IMAGE_OVERRIDE is not None:
in_image = IN_IMAGE_OVERRIDE
# Helpers
def _show_query_fn(plotx_shift, rowcols):
'helper for viz._show_res'
plotx = plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
#print('[viz] Plotting Query: pnum=%r' % (pnum,))
_kwshow = dict(draw_kpts=annote)
_kwshow.update(kwargs)
_kwshow['prefix'] = 'q'
_kwshow['res'] = res
_kwshow['pnum'] = pnum
_kwshow['cx2_color'] = cx2_color
_kwshow['draw_ell'] = annote >= 1
#_kwshow['in_image'] = in_image
show_chip(hs, **_kwshow)
#if in_image:
#roi1 = hs.cx2_roi(res.qcx)
#df2.draw_roi(roi1, bbox_color=df2.ORANGE, label='q' + hs.cidstr(res.qcx))
def _plot_matches_cxs(cx_list, plotx_shift, rowcols):
def _show_matches_fn(cx, orank, pnum):
'Helper function for drawing matches to one cx'
aug = 'rank=%r\n' % orank
#printDBG('[viz._show_res()] plotting: %r' % (pnum,))
_kwshow = dict(draw_ell=annote, draw_pts=False, draw_lines=annote,
ell_alpha=.5, all_kpts=all_kpts)
_kwshow.update(kwargs)
_kwshow['fnum'] = fnum
_kwshow['pnum'] = pnum
_kwshow['title_aug'] = aug
# If we already are showing the query dont show it here
if not show_query:
_kwshow['draw_ell'] = annote == 1
_kwshow['draw_lines'] = annote >= 1
res_show_chipres(res, hs, cx, in_image=in_image, **_kwshow)
else:
_kwshow['draw_ell'] = annote >= 1
if annote == 2:
# TODO Find a better name
_kwshow['color'] = cx2_color[cx]
_kwshow['sel_fx2'] = res.cx2_fm[cx][:, 1]
show_chip(hs, cx, in_image=in_image, **_kwshow)
annotate_chipres(hs, res, cx, in_image=in_image, show_query=not show_query)
'helper for viz._show_res to draw many cxs'
#printDBG('[viz._show_res()] Plotting Chips %s:' % hs.cidstr(cx_list))
if cx_list is None:
return
for ox, cx in enumerate(cx_list):
plotx = ox + plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
oranks = np.where(ranked_cxs == cx)[0]
if len(oranks) == 0:
orank = -1
continue
orank = oranks[0] + 1
_show_matches_fn(cx, orank, pnum)
if dosquare:
# HACK
nSubplots = nGtSubplts + nTopNSubplts
nRows, nCols = get_square_row_cols(nSubplots, 3)
nTopNCols = nGTCols = nCols
shift_topN = 1
printDBG('nRows, nCols = (%r, %r)' % (nRows, nCols))
else:
shift_topN = nGtCells
if nGtSubplts == 1:
nGTCols = 1
fig = df2.figure(fnum=fnum, pnum=(nRows, nGTCols, 1), docla=True, doclf=True)
df2.disconnect_callback(fig, 'button_press_event')
df2.plt.subplot(nRows, nGTCols, 1)
# Plot Query
if show_query:
_show_query_fn(0, (nRows, nGTCols))
# Plot Ground Truth
_plot_matches_cxs(gt_cxs, nQuerySubplts, (nRows, nGTCols))
_plot_matches_cxs(topN_cxs, shift_topN, (nRows, nTopNCols))
figtitle += ' q%s name=%s' % (hs.cidstr(res.qcx), hs.cx2_name(res.qcx))
df2.set_figtitle(figtitle, incanvas=not NO_LABEL_OVERRIDE)
# Result Interaction
if interact:
printDBG('[viz._show_res()] starting interaction')
def _ctrlclicked_cx(cx):
printDBG('ctrl+clicked cx=%r' % cx)
fnum = FNUMS['special']
fig = df2.figure(fnum=fnum, docla=True, doclf=True)
df2.disconnect_callback(fig, 'button_press_event')
viz_spatial_verification(hs, res.qcx, cx2=cx, fnum=fnum)
fig.canvas.draw()
df2.bring_to_front(fig)
def _clicked_cx(cx):
printDBG('clicked cx=%r' % cx)
fnum = FNUMS['inspect']
res.interact_chipres(hs, cx, fnum=fnum)
fig = df2.gcf()
fig.canvas.draw()
df2.bring_to_front(fig)
def _clicked_none():
# Toggle if the click is not in any axis
printDBG('clicked none')
#print(kwargs)
_show_res(hs, res, annote=(annote + 1) % 3, **kwargs)
fig.canvas.draw()
def _on_res_click(event):
'result interaction mpl event callback slot'
print('[viz] clicked result')
if event.xdata is None or event.inaxes is None:
#print('clicked outside axes')
return _clicked_none()
ax = event.inaxes
hs_viewtype = ax.__dict__.get('_hs_viewtype', '')
printDBG(event.__dict__)
printDBG('hs_viewtype=%r' % hs_viewtype)
# Clicked a specific chipres
if hs_viewtype.find('chipres') == 0:
cx = ax.__dict__.get('_hs_cx')
# Ctrl-Click
key = '' if event.key is None else event.key
print('key = %r' % key)
if key.find('control') == 0:
print('[viz] result control clicked')
return _ctrlclicked_cx(cx)
# Left-Click
else:
print('[viz] result clicked')
return _clicked_cx(cx)
df2.connect_callback(fig, 'button_press_event', _on_res_click)
df2.adjust_subplots_safe()
printDBG('[viz._show_res()] Finished')
return fig
def begin_interaction(type_, fnum):
print('[inter] starting %s interaction' % type_)
fig = df2.figure(fnum=fnum, docla=True, doclf=True)
ax = df2.gca()
df2.disconnect_callback(fig, 'button_press_event', axes=[ax])
return fig
def _sv_view(cx):
fnum = viz.FNUMS['special']
fig = df2.figure(fnum=fnum, docla=True, doclf=True)
df2.disconnect_callback(fig, 'button_press_event')
viz.viz_spatial_verification(hs, res.qcx, cx2=cx, fnum=fnum)
viz.draw()