def annotate_image(ellipses=None,
old_pts=None,
thickness=params.ellipse_thickness):
"""Return points corresponding to drawn ellipses."""
# draw ellipses
if ellipses is None:
linesegs = []
else:
linesegs = draw_ellipses(ellipses)
# draw tails
if old_pts is not None:
prevpts = {}
for frame_pts in old_pts:
for pt in frame_pts:
if prevpts.has_key(pt[2]):
prevpt = prevpts[pt[2]]
color = params.colors[pt[2] % len(params.colors)]
linesegs.append([
prevpt[0] + 1, prevpt[1] + 1, pt[0] + 1, pt[1] + 1,
color
])
prevpts[pt[2]] = pt[0:2]
return linesegs
def annotate_image( ellipses=None, old_pts=None, thickness=params.ellipse_thickness ):
"""Return points corresponding to drawn ellipses."""
# draw ellipses
if ellipses is None:
linesegs = []
else:
linesegs = draw_ellipses( ellipses )
# draw tails
if old_pts is not None:
prevpts = {}
for frame_pts in old_pts:
for pt in frame_pts:
if prevpts.has_key(pt[2]):
prevpt = prevpts[pt[2]]
color = params.colors[pt[2]%len(params.colors)]
linesegs.append([prevpt[0]+1,prevpt[1]+1,
pt[0]+1,pt[1]+1,color])
prevpts[pt[2]] = pt[0:2]
return linesegs
def get_sub_image( self, sub_type, framenumber ):
"""Do background subtraction and return a particular image type."""
wx.BeginBusyCursor()
try: wx.Yield()
except: pass # sometimes complains about recursive Yield()
# do background subtraction if necessary
if sub_type in [params.SHOW_DISTANCE,params.SHOW_THRESH,
params.SHOW_CC,params.SHOW_ELLIPSES,
params.SHOW_BACKGROUND,params.SHOW_DEV,
params.SHOW_BG_AND_DIST]:
(dfore,bw,cc,ncc) = self.sub_bg( framenumber ) # sets self.on, etc.
else:
if hasattr( self, 'dfore' ):
dfore = self.dfore
bw = self.bw
cc = self.cc
ncc = self.ncc
else:
dfore = None
bw = None
cc = None
ncc = None
line_segs = []
line_clrs = []
img_format = None
# format image in "subtraction type"
if sub_type == params.SHOW_BACKGROUND:
cntr = self.centers[self.on] if self.varying_bg else self.center
img_8 = imagesk.double2mono8(cntr,donormalize=False)
img_format = 'MONO8'
preview_range = (0,255)
elif sub_type == params.SHOW_DISTANCE:
img_8 = imagesk.double2mono8(dfore)
img_format = 'MONO8'
preview_range = (dfore.min(), dfore.max())
elif sub_type == params.SHOW_THRESH:
img_8 = imagesk.double2mono8(bw.astype(float))
img_format = 'MONO8'
preview_range = (0,1)
elif sub_type == params.SHOW_NONFORE:
isnotarena = (self.isarena == False)
img_8 = imagesk.double2mono8(isnotarena.astype(float))
img_format = 'MONO8'
preview_range = (0,1)
elif sub_type == params.SHOW_DEV:
dev = self.devs[self.on] if self.varying_bg else self.dev
mu = num.mean(dev)
sig = num.std(dev)
if sig == 0:
img_8 = imagesk.double2mono8(dev)
n1 = mu
n2 = mu
else:
n1 = max(0,mu - 3.*sig)
n2 = mu + 3.*sig
img_8 = imagesk.double2mono8(dev.clip(n1,n2))
img_format = 'MONO8'
preview_range = (n1,n2)
elif sub_type == params.SHOW_CC:
img_8,clim = colormap_image(cc)
img_format = 'RGB8'
preview_range = clim
elif sub_type == params.SHOW_ELLIPSES:
# find ellipse observations
obs = find_ellipses(dfore,cc,ncc,False)
im, stamp = params.movie.get_frame( int(framenumber) )
img_8 = imagesk.double2mono8(im,donormalize=False)
plot_linesegs = draw_ellipses(obs)
(linesegs,linecolors) = \
imagesk.separate_linesegs_colors(plot_linesegs)
img_8 = imagesk.double2mono8(im,donormalize=False)
img_format = 'MONO8'
preview_range = (0,255)
line_segs.extend( linesegs )
line_clrs.extend( linecolors )
elif sub_type == params.SHOW_BG_AND_DIST:
cntr = self.centers[self.on] if self.varying_bg else self.center
img = Image.fromarray(imagesk.double2mono8(cntr,donormalize=False)).convert('RGB')
img.paste((0,255,0), None, Image.fromarray(imagesk.double2mono8(dfore)))
img_8 = num.array(img)
img_format = 'RGB8'
preview_range = (0,255)
elif sub_type in params.SHOW_EXPBGFGMODEL:
# check for expbgfgmodel
if not params.use_expbgfgmodel or not hasattr(self,'expbgfgmodel') or \
self.expbgfgmodel is None:
resp = wx.MessageBox("No prior model loaded.","No prior model loaded",wx.OK)
else:
if sub_type == params.SHOW_EXPBGFGMODEL_LLR:
# read the current image, classify pixels
im, stamp = params.movie.get_frame( int(framenumber) )
llr = self.expbgfgmodel_llr(im)
img_8,clim = colormap_image(llr)
img_format = 'RGB'
preview_range = clim
elif sub_type == params.SHOW_EXPBGFGMODEL_ISBACK:
im, stamp = params.movie.get_frame( int(framenumber) )
isback = self.thresh_expbgfgmodel_llr(im)
img_8 = imagesk.double2mono8(isback.astype(float))
img_format = 'MONO8'
preview_range = (0,1)
elif sub_type == params.SHOW_EXPBGFGMODEL_BGMU:
img_8 = imagesk.double2mono8(self.expbgfgmodel.bg_mu,donormalize=False)
img_format = 'MONO8'
preview_range = (0,255)
elif sub_type == params.SHOW_EXPBGFGMODEL_FGMU:
img_8 = imagesk.double2mono8(self.expbgfgmodel.fg_mu,donormalize=False)
img_format = 'MONO8'
preview_range = (0,255)
elif sub_type == params.SHOW_EXPBGFGMODEL_BGSIGMA:
mu = num.mean(self.expbgfgmodel.bg_sigma)
sig = num.std(self.expbgfgmodel.bg_sigma)
if sig == 0:
n1 = mu
n2 = mu
img_8 = imagesk.double2mono8(self.expbgfgmodel.bg_sigma)
else:
n1 = max(0,mu - 3.*sig)
n2 = mu + 3.*sig
img_8 = imagesk.double2mono8(self.expbgfgmodel.bg_sigma.clip(n1,n2))
img_format = 'MONO8'
preview_range = (n1,n2)
elif sub_type == params.SHOW_EXPBGFGMODEL_FGSIGMA:
mu = num.mean(self.expbgfgmodel.fg_sigma)
sig = num.std(self.expbgfgmodel.fg_sigma)
if sig == 0:
img_8 = imagesk.double2mono8(self.expbgfgmodel.fg_sigma)
n1 = mu
n2 = mu
else:
n1 = max(0,mu - 3.*sig)
n2 = mu + 3.*sig
img_8 = imagesk.double2mono8(self.expbgfgmodel.fg_sigma.clip(n1,n2))
img_format = 'MONO8'
preview_range = (n1,n2)
elif sub_type == params.SHOW_EXPBGFGMODEL_FRACFRAMESISBACK:
if not hasattr(self,'fracframesisback') or self.fracframesisback is None:
resp = wx.MessageBox("fracframesisback not yet computed","fracframesisback Not Computed",wx.OK)
return
img_8,clim = colormap_image(self.fracframesisback)
img_format = 'RGB8'
preview_range = clim
elif sub_type == params.SHOW_EXPBGFGMODEL_MISSINGDATA:
if not hasattr(self,'fracframesisback') or self.fracframesisback is None:
resp = wx.MessageBox("fracframesisback not yet computed","fracframesisback Not Computed",wx.OK)
return
missingdata = self.fracframesisback <= params.min_frac_frames_isback
img_8 = imagesk.double2mono8(missingdata.astype(float))
img_format = 'MONO8'
preview_range = (0,1)
wx.EndBusyCursor()
return img_8, img_format, line_segs, line_clrs, dfore, bw, cc, ncc, preview_range
def get_sub_image(self, sub_type, framenumber):
"""Do background subtraction and return a particular image type."""
wx.BeginBusyCursor()
try:
wx.Yield()
except:
pass # sometimes complains about recursive Yield()
# do background subtraction if necessary
if sub_type in [
params.SHOW_DISTANCE, params.SHOW_THRESH, params.SHOW_CC,
params.SHOW_ELLIPSES, params.SHOW_BACKGROUND, params.SHOW_DEV,
params.SHOW_BG_AND_DIST
]:
(dfore, bw, cc,
ncc) = self.sub_bg(framenumber) # sets self.on, etc.
else:
if hasattr(self, 'dfore'):
dfore = self.dfore
bw = self.bw
cc = self.cc
ncc = self.ncc
else:
dfore = None
bw = None
cc = None
ncc = None
line_segs = []
line_clrs = []
img_format = None
# format image in "subtraction type"
if sub_type == params.SHOW_BACKGROUND:
cntr = self.centers[self.on] if self.varying_bg else self.center
img_8 = imagesk.double2mono8(cntr, donormalize=False)
img_format = 'MONO8'
preview_range = (0, 255)
elif sub_type == params.SHOW_DISTANCE:
img_8 = imagesk.double2mono8(dfore)
img_format = 'MONO8'
preview_range = (dfore.min(), dfore.max())
elif sub_type == params.SHOW_THRESH:
img_8 = imagesk.double2mono8(bw.astype(float))
img_format = 'MONO8'
preview_range = (0, 1)
elif sub_type == params.SHOW_NONFORE:
isnotarena = (self.isarena == False)
img_8 = imagesk.double2mono8(isnotarena.astype(float))
img_format = 'MONO8'
preview_range = (0, 1)
elif sub_type == params.SHOW_DEV:
dev = self.devs[self.on] if self.varying_bg else self.dev
mu = num.mean(dev)
sig = num.std(dev)
if sig == 0:
img_8 = imagesk.double2mono8(dev)
n1 = mu
n2 = mu
else:
n1 = max(0, mu - 3. * sig)
n2 = mu + 3. * sig
img_8 = imagesk.double2mono8(dev.clip(n1, n2))
img_format = 'MONO8'
preview_range = (n1, n2)
elif sub_type == params.SHOW_CC:
img_8, clim = colormap_image(cc)
img_format = 'RGB8'
preview_range = clim
elif sub_type == params.SHOW_ELLIPSES:
# find ellipse observations
obs = find_ellipses(dfore, cc, ncc, False)
im, stamp = params.movie.get_frame(int(framenumber))
img_8 = imagesk.double2mono8(im, donormalize=False)
plot_linesegs = draw_ellipses(obs)
(linesegs,linecolors) = \
imagesk.separate_linesegs_colors(plot_linesegs)
img_8 = imagesk.double2mono8(im, donormalize=False)
img_format = 'MONO8'
preview_range = (0, 255)
line_segs.extend(linesegs)
line_clrs.extend(linecolors)
elif sub_type == params.SHOW_BG_AND_DIST:
cntr = self.centers[self.on] if self.varying_bg else self.center
img = Image.fromarray(imagesk.double2mono8(
cntr, donormalize=False)).convert('RGB')
img.paste((0, 255, 0), None,
Image.fromarray(imagesk.double2mono8(dfore)))
img_8 = num.array(img)
img_format = 'RGB8'
preview_range = (0, 255)
elif sub_type in params.SHOW_EXPBGFGMODEL:
# check for expbgfgmodel
if not params.use_expbgfgmodel or not hasattr(self,'expbgfgmodel') or \
self.expbgfgmodel is None:
resp = wx.MessageBox("No prior model loaded.",
"No prior model loaded", wx.OK)
else:
if sub_type == params.SHOW_EXPBGFGMODEL_LLR:
# read the current image, classify pixels
im, stamp = params.movie.get_frame(int(framenumber))
llr = self.expbgfgmodel_llr(im)
img_8, clim = colormap_image(llr)
img_format = 'RGB'
preview_range = clim
elif sub_type == params.SHOW_EXPBGFGMODEL_ISBACK:
im, stamp = params.movie.get_frame(int(framenumber))
isback = self.thresh_expbgfgmodel_llr(im)
img_8 = imagesk.double2mono8(isback.astype(float))
img_format = 'MONO8'
preview_range = (0, 1)
elif sub_type == params.SHOW_EXPBGFGMODEL_BGMU:
img_8 = imagesk.double2mono8(self.expbgfgmodel.bg_mu,
donormalize=False)
img_format = 'MONO8'
preview_range = (0, 255)
elif sub_type == params.SHOW_EXPBGFGMODEL_FGMU:
img_8 = imagesk.double2mono8(self.expbgfgmodel.fg_mu,
donormalize=False)
img_format = 'MONO8'
preview_range = (0, 255)
elif sub_type == params.SHOW_EXPBGFGMODEL_BGSIGMA:
mu = num.mean(self.expbgfgmodel.bg_sigma)
sig = num.std(self.expbgfgmodel.bg_sigma)
if sig == 0:
n1 = mu
n2 = mu
img_8 = imagesk.double2mono8(
self.expbgfgmodel.bg_sigma)
else:
n1 = max(0, mu - 3. * sig)
n2 = mu + 3. * sig
img_8 = imagesk.double2mono8(
self.expbgfgmodel.bg_sigma.clip(n1, n2))
img_format = 'MONO8'
preview_range = (n1, n2)
elif sub_type == params.SHOW_EXPBGFGMODEL_FGSIGMA:
mu = num.mean(self.expbgfgmodel.fg_sigma)
sig = num.std(self.expbgfgmodel.fg_sigma)
if sig == 0:
img_8 = imagesk.double2mono8(
self.expbgfgmodel.fg_sigma)
n1 = mu
n2 = mu
else:
n1 = max(0, mu - 3. * sig)
n2 = mu + 3. * sig
img_8 = imagesk.double2mono8(
self.expbgfgmodel.fg_sigma.clip(n1, n2))
img_format = 'MONO8'
preview_range = (n1, n2)
elif sub_type == params.SHOW_EXPBGFGMODEL_FRACFRAMESISBACK:
if not hasattr(self, 'fracframesisback'
) or self.fracframesisback is None:
resp = wx.MessageBox(
"fracframesisback not yet computed",
"fracframesisback Not Computed", wx.OK)
return
img_8, clim = colormap_image(self.fracframesisback)
img_format = 'RGB8'
preview_range = clim
elif sub_type == params.SHOW_EXPBGFGMODEL_MISSINGDATA:
if not hasattr(self, 'fracframesisback'
) or self.fracframesisback is None:
resp = wx.MessageBox(
"fracframesisback not yet computed",
"fracframesisback Not Computed", wx.OK)
return
missingdata = self.fracframesisback <= params.min_frac_frames_isback
img_8 = imagesk.double2mono8(missingdata.astype(float))
img_format = 'MONO8'
preview_range = (0, 1)
wx.EndBusyCursor()
return img_8, img_format, line_segs, line_clrs, dfore, bw, cc, ncc, preview_range
def ShowImage(self):
if DEBUG_TRACKINGSETTINGS: print 'ShowImage ' + str(self.show_frame)
try:
wx.Yield()
except:
pass # can be recursive sometimes in Windows
wx.BeginBusyCursor()
im, stamp = self.bg_imgs.movie.get_frame(int(self.show_frame))
windowsize = [
self.img_panel.GetRect().GetHeight(),
self.img_panel.GetRect().GetWidth()
]
self.GetBgImage()
if self.img_chosen == SHOW_UNFILTERED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_UNFILTERED_OBSERVATIONS'
obs_unfiltered = self.GetObsUnfiltered()
plot_linesegs = draw_ellipses(obs_unfiltered)
elif self.img_chosen == SHOW_FILTERED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_FILTERED_OBSERVATIONS'
obs_filtered = self.GetObsFiltered()
plot_linesegs = draw_ellipses(obs_filtered)
elif self.img_chosen == SHOW_SMALL_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_SMALL_OBSERVATIONS'
obs_unfiltered = self.GetObsUnfiltered()
obs_small = []
for obs in obs_unfiltered:
if obs.area() < params.params.minshape.area:
obs_small.append(obs)
plot_linesegs = draw_ellipses(obs_small)
elif self.img_chosen == SHOW_LARGE_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_LARGE_OBSERVATIONS'
obs_unfiltered = self.GetObsUnfiltered()
obs_large = []
for obs in obs_unfiltered:
if obs.area() > params.params.maxshape.area:
obs_large.append(obs)
plot_linesegs = draw_ellipses(obs_large)
elif self.img_chosen == SHOW_DELETED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_DELETED_OBSERVATIONS'
(obs_unfiltered, obs_deleted) = self.GetObsUnfiltered('diddelete')
plot_linesegs = draw_ellipses(obs_deleted)
elif self.img_chosen == SHOW_SPLIT_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_SPLIT_OBSERVATIONS'
(obs_unfiltered, obs_split) = self.GetObsUnfiltered('didsplit')
plot_linesegs = draw_ellipses(obs_split)
elif self.img_chosen == SHOW_MERGED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_MERGED_OBSERVATIONS'
(obs_unfiltered, obs_merge) = self.GetObsUnfiltered('didmerge')
plot_linesegs = draw_ellipses(obs_merge)
elif self.img_chosen == SHOW_LOWERED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_LOWERED_OBSERVATIONS'
(obs_unfiltered,
obs_lowered) = self.GetObsUnfiltered('didlowerthresh')
plot_linesegs = draw_ellipses(obs_lowered)
# MAXJUMP
elif self.img_chosen == SHOW_MAXJUMP:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_MAXJUMP'
# either grab or compute observations
obs_filtered = self.GetObsFiltered()
plot_linesegs = draw_ellipses(obs_filtered)
# draw circles
for i, obs in enumerate(obs_filtered):
plot_new_stuff = imagesk.draw_circle(
obs.center.x, obs.center.y, params.params.max_jump * 2.,
params.params.colors[i % len(params.params.colors)])
plot_linesegs.extend(plot_new_stuff)
plot_new_stuff = imagesk.draw_circle(
obs.center.x, obs.center.y, params.params.min_jump,
params.params.colors[i % len(params.params.colors)])
plot_linesegs.extend(plot_new_stuff)
elif self.img_chosen == SHOW_MOTIONMODEL:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_MOTIONMODEL'
(target_prev, target_curr, target_pred) = self.GetTargetMotion()
# show the next frame, if there is one
nextframe = num.minimum(int(self.show_frame + 1),
params.params.n_frames - 1)
im, stamp = self.bg_imgs.movie.get_frame(nextframe)
# draw previous positions
plot_linesegs = draw_ellipses(target_prev)
# draw current positions
plot_new_stuff = draw_ellipses(target_curr)
plot_linesegs.extend(plot_new_stuff)
# draw predicted positions
plot_new_stuff = draw_ellipses(target_pred)
plot_linesegs.extend(plot_new_stuff)
scaleunit = params.params.max_jump / params.params.DRAW_MOTION_SCALE
parcolor = [0, 255, 0]
perpcolor = [0, 255, 0]
anglecolor = [0, 0, 255]
for i in target_pred.iterkeys():
# compute direction of motion
vx = target_pred[i].center.x - target_curr[i].center.x
vy = target_pred[i].center.y - target_curr[i].center.y
thetamotion = num.arctan2(vy, vx)
# angle
theta = target_pred[i].angle
# we want to choose to add pi if that makes difference from motion direction smaller
dtheta = abs(((theta - thetamotion + num.pi) % (2. * num.pi)) -
num.pi)
if dtheta > (num.pi / 2.):
theta += num.pi
# compute end points of parallel motion
x0 = target_pred[i].center.x + scaleunit * num.cos(theta)
x1 = target_pred[i].center.x - scaleunit * num.cos(theta)
y0 = target_pred[i].center.y + scaleunit * num.sin(theta)
y1 = target_pred[i].center.y - scaleunit * num.sin(theta)
# add parallel motion annotation line
plot_new_stuff = imagesk.draw_line(x0 + 1, y0 + 1, x1 + 1,
y1 + 1, parcolor)
plot_linesegs.extend(plot_new_stuff)
# compute end points of perpendicular motion
x0 = target_pred[i].center.x + scaleunit * num.cos(num.pi /
2. + theta)
x1 = target_pred[i].center.x - scaleunit * num.cos(num.pi /
2. + theta)
y0 = target_pred[i].center.y + scaleunit * num.sin(num.pi /
2. + theta)
y1 = target_pred[i].center.y - scaleunit * num.sin(num.pi /
2. + theta)
# add perpendicular motion annotation line
plot_new_stuff = imagesk.draw_line(x0 + 1, y0 + 1, x1 + 1,
y1 + 1, perpcolor)
plot_linesegs.extend(plot_new_stuff)
# compute end points of angular motion
if params.params.ang_dist_wt > 0:
dtheta = scaleunit * num.sqrt(
1. / params.params.ang_dist_wt)
if dtheta >= (num.pi / 2.):
print 'dtheta is more than pi/2'
else:
theta0 = theta - dtheta
theta1 = theta + dtheta
# draw arc
plot_new_stuff = imagesk.draw_arc(
target_pred[i].center.x, target_pred[i].center.y,
scaleunit / 2, theta0, theta1, anglecolor)
plot_linesegs.extend(plot_new_stuff)
im = imagesk.double2mono8(im, donormalize=False)
linesegs, im = imagesk.zoom_linesegs_and_image(plot_linesegs, im,
self.zoomaxes)
(linesegs, linecolors) = imagesk.separate_linesegs_colors(linesegs)
self.img_wind.update_image_and_drawings('trackset',
im,
format='MONO8',
linesegs=linesegs,
lineseg_colors=linecolors)
self.img_wind.Refresh(eraseBackground=False)
self.frame_number_text.SetLabel('Frame %d' % self.show_frame)
if self.info == True:
self.ShowInfo(None, None)
wx.EndBusyCursor()
if DEBUG_TRACKINGSETTINGS: sys.stdout.flush()
def ShowImage(self):
if DEBUG_TRACKINGSETTINGS: print 'ShowImage ' + str(self.show_frame)
try:
wx.Yield()
except: pass # can be recursive sometimes in Windows
wx.BeginBusyCursor()
im, stamp = params.params.movie.get_frame( int(self.show_frame) )
windowsize = [self.img_panel.GetRect().GetHeight(),self.img_panel.GetRect().GetWidth()]
self.GetBgImage()
if self.img_chosen == SHOW_UNFILTERED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_UNFILTERED_OBSERVATIONS'
obs_unfiltered = self.GetObsUnfiltered()
plot_linesegs = draw_ellipses(obs_unfiltered)
elif self.img_chosen == SHOW_FILTERED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_FILTERED_OBSERVATIONS'
obs_filtered = self.GetObsFiltered()
plot_linesegs = draw_ellipses(obs_filtered)
elif self.img_chosen == SHOW_SMALL_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_SMALL_OBSERVATIONS'
obs_unfiltered = self.GetObsUnfiltered()
obs_small = []
for obs in obs_unfiltered:
if obs.area < params.params.minshape.area:
obs_small.append(obs)
plot_linesegs = draw_ellipses(obs_small)
elif self.img_chosen == SHOW_LARGE_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_LARGE_OBSERVATIONS'
obs_unfiltered = self.GetObsUnfiltered()
obs_large = []
for obs in obs_unfiltered:
if obs.area > params.params.maxshape.area:
obs_large.append(obs)
plot_linesegs = draw_ellipses(obs_large)
elif self.img_chosen == SHOW_DELETED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_DELETED_OBSERVATIONS'
(obs_unfiltered,obs_deleted) = self.GetObsUnfiltered('diddelete')
plot_linesegs = draw_ellipses(obs_deleted)
elif self.img_chosen == SHOW_SPLIT_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_SPLIT_OBSERVATIONS'
(obs_unfiltered,obs_split) = self.GetObsUnfiltered('didsplit')
plot_linesegs = draw_ellipses(obs_split)
elif self.img_chosen == SHOW_MERGED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_MERGED_OBSERVATIONS'
(obs_unfiltered,obs_merge) = self.GetObsUnfiltered('didmerge')
plot_linesegs = draw_ellipses(obs_merge)
elif self.img_chosen == SHOW_LOWERED_OBSERVATIONS:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_LOWERED_OBSERVATIONS'
(obs_unfiltered,obs_lowered) = self.GetObsUnfiltered('didlowerthresh')
plot_linesegs = draw_ellipses(obs_lowered)
# MAXJUMP
elif self.img_chosen == SHOW_MAXJUMP:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_MAXJUMP'
# either grab or compute observations
obs_filtered = self.GetObsFiltered()
plot_linesegs = draw_ellipses(obs_filtered)
# draw circles
for i,obs in enumerate(obs_filtered):
plot_new_stuff = imagesk.draw_circle(obs.center.x,
obs.center.y,params.params.max_jump*2.,
params.params.colors[i%len(params.params.colors)])
plot_linesegs.extend(plot_new_stuff)
plot_new_stuff = imagesk.draw_circle(obs.center.x,
obs.center.y,params.params.min_jump,
params.params.colors[i%len(params.params.colors)])
plot_linesegs.extend(plot_new_stuff)
elif self.img_chosen == SHOW_MOTIONMODEL:
if DEBUG_TRACKINGSETTINGS: print 'SHOW_MOTIONMODEL'
(target_prev,target_curr,target_pred) = self.GetTargetMotion()
# show the next frame, if there is one
nextframe = num.minimum(int(self.show_frame+1),params.params.n_frames-1)
im, stamp = params.params.movie.get_frame(nextframe)
# draw previous positions
plot_linesegs = draw_ellipses(target_prev)
# draw current positions
plot_new_stuff = draw_ellipses(target_curr,colors=[[255,255,0]])
plot_linesegs.extend(plot_new_stuff)
# draw predicted positions
plot_new_stuff = draw_ellipses(target_pred)
plot_linesegs.extend(plot_new_stuff)
scaleunit = params.params.max_jump / params.params.DRAW_MOTION_SCALE
parcolor = [0,255,0]
perpcolor = [0,255,0]
anglecolor = [0,0,255]
for i in target_pred.iterkeys():
# compute direction of motion
vx = target_pred[i].center.x - target_curr[i].center.x
vy = target_pred[i].center.y - target_curr[i].center.y
thetamotion = num.arctan2(vy,vx)
# angle
theta = target_pred[i].angle
# we want to choose to add pi if that makes difference from motion direction smaller
dtheta = abs( ((theta - thetamotion + num.pi) % (2.*num.pi)) - num.pi )
if dtheta > (num.pi/2.):
theta += num.pi
# compute end points of parallel motion
x0 = target_pred[i].center.x + scaleunit*num.cos(theta)
x1 = target_pred[i].center.x - scaleunit*num.cos(theta)
y0 = target_pred[i].center.y + scaleunit*num.sin(theta)
y1 = target_pred[i].center.y - scaleunit*num.sin(theta)
# add parallel motion annotation line
plot_new_stuff = imagesk.draw_line(x0+1,y0+1,x1+1,y1+1,parcolor)
plot_linesegs.extend(plot_new_stuff)
# compute end points of perpendicular motion
x0 = target_pred[i].center.x + scaleunit*num.cos(num.pi/2.+theta)
x1 = target_pred[i].center.x - scaleunit*num.cos(num.pi/2.+theta)
y0 = target_pred[i].center.y + scaleunit*num.sin(num.pi/2.+theta)
y1 = target_pred[i].center.y - scaleunit*num.sin(num.pi/2.+theta)
# add perpendicular motion annotation line
plot_new_stuff = imagesk.draw_line(x0+1,y0+1,x1+1,y1+1,perpcolor)
plot_linesegs.extend(plot_new_stuff)
# compute end points of angular motion
if params.params.ang_dist_wt > 0:
dtheta = scaleunit*num.sqrt(1./params.params.ang_dist_wt)
if dtheta >= (num.pi/2.):
print 'dtheta is more than pi/2'
else:
theta0 = theta - dtheta
theta1 = theta + dtheta
# draw arc
plot_new_stuff = imagesk.draw_arc(target_pred[i].center.x,
target_pred[i].center.y,
scaleunit/2,
theta0,theta1,
anglecolor)
plot_linesegs.extend(plot_new_stuff)
im = imagesk.double2mono8(im,donormalize=False)
linesegs,im = imagesk.zoom_linesegs_and_image(plot_linesegs,im,self.zoomaxes)
(linesegs,linecolors) = imagesk.separate_linesegs_colors(linesegs)
self.img_wind.update_image_and_drawings('trackset',
im,
format='MONO8',
linesegs=linesegs,
lineseg_colors=linecolors
)
self.img_wind.Refresh(eraseBackground=False)
self.frame_number_text.SetLabel('Frame %d'%self.show_frame)
if self.info == True:
self.ShowInfo( None, None )
wx.EndBusyCursor()
if DEBUG_TRACKINGSETTINGS: sys.stdout.flush()