def cvpred(X1, X2):
"""Make prediction (target) based on two observations.
Expects two EllipseLists, returns a single EllipseList."""
X3 = ell.TargetList()
# set position and size as an extrapolation
for ee in X2.iterkeys():
if X1.hasItem(ee):
# only use the cv prediction if not jumping
dx = X2[ee].center.x - X1[ee].center.x
dy = X2[ee].center.y - X1[ee].center.y
centerd = num.sqrt((dx**2. + dy**2.))
if centerd >= params.min_jump:
new_x = X2[ee].center.x
new_y = X2[ee].center.y
dangle = X2[ee].angle
else:
new_x = X2[ee].center.x + (1. - params.dampen) * dx
new_y = X2[ee].center.y + (1. - params.dampen) * dy
dangle = ((X2[ee].angle - X1[ee].angle + num.pi/2.) \
% (num.pi)) - (num.pi/2.)
new_w = X2[ee].size.width
new_h = X2[ee].size.height
new_angle = X2[ee].angle + (1. - params.angle_dampen) * dangle
X3.append(
ell.Ellipse(new_x, new_y, new_w, new_h, new_angle,
X2[ee].identity))
else:
X3.append(X2[ee].copy())
return X3
return h
try:
os.remove('tmp.ann')
except:
pass
tracks = ann.AnnotationFile('tmp.ann', None, True, False, False)
tracks.InitializeData(0, -1)
tracks.InitializeBufferForTracking(0)
# tracks = []
# frame 0
tracks.append(ell.TargetList())
# just one ellipse with id = 0
tracks[0][0] = ell.Ellipse(10., 10., 1., 2., num.pi / 3, 0., 0)
tracks[0][0].compute_area()
# frame 1
# just one ellipse with id = 0
tracks.append(ell.TargetList())
tracks[1][0] = tracks[0][0].copy()
tracks[1][0].x += 10.
tracks[1][0].y += 10.
# frame 2
# detection missed at pred
# new ellipse at another location
tracks.append(ell.TargetList())
#tracks[2][1] = ell.Ellipse(20.,20.,1.,2.,num.pi/3,0.,1)
prev = tracks[0].copy()
curr = tracks[1].copy()
pred = matchidentities.cvpred(prev, curr)
# append the targets that didn't match any observation
for oo in range(len(obs)):
if unass_obs[oo]:
obs[oo].identity = params.nids
params.nids += 1
flies.append(obs[oo])
return (flies, obs_for_target, unass_obs)
tracks_true = []
cc = []
# frame 0
tracks_true.append(ell.TargetList())
tracks_true[0][0] = ell.Ellipse(50., 10., 2., 4., num.pi / 3, 0., 0)
tracks_true[0][0].compute_area()
# frame 1
tracks_true.append(ell.TargetList())
tracks_true[1][0] = ell.Ellipse(50., 20., 2., 4., num.pi / 3, 0., 0)
tracks_true[1][0].compute_area()
for t in range(2, 9):
tracks_true.append(matchidentities.cvpred(tracks_true[-2],
tracks_true[-1]))
bw = []
bounds = [0, 100, 0, 100]
nr = bounds[1] - bounds[0]
nc = bounds[3] - bounds[2]
for track_true in tracks_true:
tmp = num.zeros((nr, nc), dtype=bool)
def add_fly(annfile, x, y, theta):
flies = ell.TargetList()
flies.append(ell.Ellipse(x, y, 5., 10., theta, 25., 0))
annfile.append(flies)
# append the targets that didn't match any observation
for oo in range(len(obs)):
if unass_obs[oo]:
obs[oo].identity = params.nids
params.nids += 1
flies.append(obs[oo])
return (flies, obs_for_target, unass_obs)
tracks_true = []
cc = []
# frame 0
tracks_true.append(ell.TargetList())
tracks_true[0][0] = ell.Ellipse(37., 70., 2., 4., num.pi / 3, 0., 0)
tracks_true[0][0].compute_area()
tracks_true[0][1] = ell.Ellipse(60., 70., 2., 4., num.pi / 3, 0., 1)
tracks_true[0][1].compute_area()
# frame 1
tracks_true.append(ell.TargetList())
tracks_true[1][0] = ell.Ellipse(37., 62., 2., 4., num.pi / 3, 0., 0)
tracks_true[1][0].compute_area()
tracks_true[1][1] = ell.Ellipse(53., 62., 2., 4., num.pi / 3, 0., 1)
tracks_true[1][1].compute_area()
for t in range(2, 8):
tracks_true.append(matchidentities.cvpred(tracks_true[-2],
tracks_true[-1]))
bw = []
bounds = [0, 100, 0, 100]