def __init__(self, shape, n=1, fovea_shape=None, fill_method='smudge'):
"""
Arguments
---------
shape - Expected shape of disparity images
n - Number of past frames to retain
fovea_shape - Shape of foveal region to remember (None=whole image)
fill_method - default 'smudge' works fine and is fast, other options
are 'none' or 'interp' (which is way too slow)
"""
self.shape = shape
self.fovea_shape = fovea_shape
self.n = n
calib = Calib()
self.disp2imu = calib.get_disp2imu()
self.imu2disp = calib.get_imu2disp()
self.past_position = []
self.past_disparity = []
self.transforms = []
assert fill_method in ('smudge', 'interp', 'none')
self.fill_method = fill_method
def __init__(self, shape, n=1, fovea_shape=None, fill_method='smudge'):
"""
Arguments
---------
shape - Expected shape of disparity images
n - Number of past frames to retain
fovea_shape - Shape of foveal region to remember (None=whole image)
fill_method - default 'smudge' works fine and is fast, other options
are 'none' or 'interp' (which is way too slow)
"""
self.shape = shape
self.fovea_shape = fovea_shape
self.n = n
calib = Calib()
self.disp2imu = calib.get_disp2imu()
self.imu2disp = calib.get_imu2disp()
self.past_position = []
self.past_disparity = []
self.transforms = []
assert fill_method in ('smudge', 'interp', 'none')
self.fill_method = fill_method
print(iters)
print(errors)
idx = errors.index(min(errors))
return down_factors[idx], iters[idx], fovea_shapes[idx]
def get_coarse_subwindow():
pass
def get_seed():
pass
if __name__ == '__main__':
plt.ion()
calib = Calib()
disp2imu = calib.get_disp2imu()
imu2disp = calib.get_imu2disp()
drive = 51
video = load_stereo_video(drive)
positions = load_video_odometry(drive)
initial = video[0]
fig = plt.figure(1)
fig.clf()
ax_disp = plt.gca()
plot_disp = ax_disp.imshow(mean_disparity(drive, n_disp), vmin=0, vmax=n_disp)
fovea_ij = 100, 600
time_budget = .2
