def chip_interaction(hs, cx, notes, fnum=1, **kwargs):
chip_info_locals = dev.chip_info(hs, cx)
chip_title = chip_info_locals['cidstr']+' '+chip_info_locals['name']
chip_xlabel = chip_info_locals['gname']
class State(DynStruct):
def __init__(state):
super(State, state).__init__()
state.reset()
def reset(state):
state.res = None
state.scale_min = None
state.scale_max = None
state.fnum = 1
state.fnum_offset = 1
state = State()
state.fnum = fnum
fx_ptr = [0]
hprint = helpers.horiz_print
kpts = hs.get_kpts(cx)
scale = np.sqrt(kpts.T[2]*kpts.T[4])
desc = hs.get_desc(cx)
rchip = hs.get_chip(cx)
# Start off keypoints with no filters
is_valid = np.ones(len(kpts), dtype=bool)
def update_valid(reset=False):
print('[interact] updating valid')
if reset is True:
state.reset()
is_valid[:] = True
if state.scale_min:
is_valid[:] = np.bitwise_and(scale >= state.scale_min, is_valid)
if state.scale_max:
is_valid[:] = np.bitwise_and(scale <= state.scale_max, is_valid)
print(state)
print('%d valid keypoints' % sum(is_valid))
print('kpts scale ' + helpers.printable_mystats(scale[is_valid]))
select_ith_keypoint(fx_ptr[0])
def keypoint_info(fx):
kp = kpts[fx]
print(kp)
x,y,a,c,d = kp
A = np.array(([a,0],[c,d]))
print('--kp info--')
invA = np.linalg.inv(A)
def select_ith_keypoint(fx):
print('-------------------------------------------')
print('[interact] viewing ith=%r keypoint' % fx)
kp = kpts[fx]
sift = desc[fx]
np.set_printoptions(precision=5)
df2.cla()
fig1 = df2.figure(state.fnum, **kwargs)
df2.imshow(rchip, pnum=(2,1,1))
#df2.imshow(rchip, pnum=(1,2,1), title='inv(sqrtm(invE*)')
#df2.imshow(rchip, pnum=(1,2,2), title='inv(A)')
ell_args = {'ell_alpha':.4, 'ell_linewidth':1.8, 'rect':False}
df2.draw_kpts2(kpts[is_valid], ell_color=df2.ORANGE, **ell_args)
df2.draw_kpts2(kpts[fx:fx+1], ell_color=df2.BLUE, **ell_args)
ax = df2.gca()
#ax.set_title(str(fx)+' old=b(inv(sqrtm(invE*)) and new=o(A=invA)')
scale = np.sqrt(kp[2]*kp[4])
printops = np.get_printoptions()
np.set_printoptions(precision=1)
ax.set_title(chip_title)
ax.set_xlabel(chip_xlabel)
extract_patch.draw_keypoint_patch(rchip, kp, sift, pnum=(2,2,3))
ax = df2.gca()
ax.set_title('affine feature\nfx=%r scale=%.1f' % (fx, scale))
extract_patch.draw_keypoint_patch(rchip, kp, sift, warped=True, pnum=(2,2,4))
ax = df2.gca()
ax.set_title('warped feature\ninvA=%r ' % str(kp))
golden_wh = lambda x:map(int,map(round,(x*.618 , x*.312)))
Ooo_50_50 = {'num_rc':(1,1), 'wh':golden_wh(1400*2)}
np.set_printoptions(**printops)
#df2.present(**Ooo_50_50)
#df2.update()
fig1.show()
fig1.canvas.draw()
#df2.show()
fig = df2.figure(state.fnum )
xy = kpts.T[0:2].T
# Flann doesn't help here at all
use_flann = False
flann_ptr = [None]
def on_click(event):
if event.xdata is None: return
print('[interact] button=%d, x=%d, y=%d, xdata=%f, ydata=%f'%(
event.button, event.x, event.y, event.xdata, event.ydata))
x,y = event.xdata, event.ydata
if not use_flann:
dist = (kpts.T[0] - x)**2 + (kpts.T[1] - y)**2
fx_ptr[0] = dist.argsort()[0]
select_ith_keypoint(fx_ptr[0])
else:
flann, = flann_ptr
if flann is None:
flann = pyflann.FLANN()
flann.build_index(xy, algorithm='kdtree', trees=1)
query = np.array(((x,y)))
knnx, kdist = flann.nn_index(query, 1, checks=8)
fx_ptr[0]=knnx[0]
select_ith_keypoint(fx_ptr[0])
print('>>>')
callback_id = fig.canvas.mpl_connect('button_press_event', on_click)
select_ith_keypoint(fx_ptr[0])
query_cfg = ds.QueryConfig(hs, **kwargs)
while True:
try:
print('>>>')
raw = raw_input('enter a chip-interaction command (q to exit, h for help)\n>>>')
print('>>>')
ans = raw.split(' ')
if len(ans) == 0: continue
cmd = ans[0]
if cmd in ['e', 'exit']: break;
elif cmd == 'n':
fx_ptr[0] += 1
select_ith_keypoint(fx_ptr[0])
elif cmd in ['q', 'query']:
print(query_cfg)
print(query_cfg.get_uid())
res = hs.query(cx, query_cfg=query_cfg, use_cache=False)
state.res = res
resfnum = state.fnum + state.fnum_offset
res.show_topN(hs, fnum=resfnum)
df2.update()
#fig_res = df2.figure(fnum=resfnum)
#fig_res.show()
#fig_res.canvas.draw()
elif cmd == 'K':
query_cfg.update_cfg(K=int(ans[1]))
elif cmd == 'svoff':
query_cfg.update_cfg(sv_on=False)
elif cmd == 'svon':
query_cfg.update_cfg(sv_on=True)
elif cmd == 'test':
query_cfg.update_cfg(sv_on=True, K=20, use_chip_extent=True)
elif cmd in ['m', 'mytest']:
mycmd = open('mytest.py').read();
print(mycmd)
exec mycmd in locals(), globals()
print(query_cfg)
res = hs.query(cx, query_cfg=query_cfg, use_cache=False)
state.res = res
resfnum = state.fnum + state.fnum_offset
res.show_topN(hs, fnum=resfnum)
df2.update()
elif cmd == 'test2':
query_cfg.update_cfg(sv_on=True, K=20, use_chip_extent=True, xy_thresh=.1)
#query_cfg.update_cfg(sv_on=True, K=20, use_chip_extent=False)
elif cmd == 'reset':
update_valid(reset=True)
elif cmd in ['fig']:
state.fnum_offset += 1
elif cmd in ['smin', 'scale_min']:
state.scale_min = int(ans[1])
update_valid()
elif cmd in ['smax', 'scale_max']:
state.scale_max = int(ans[1])
update_valid()
else:
print('I dont understand the answer. I hope you know what you are doing');
print(raw)
exec raw in globals(), locals()
print('>>>')
except Exception as ex:
print(repr(ex))
if 'doraise' in vars():
raise
