# determine msmt probability from sample vs from new object
prepped_sample = prepSample(sample)
llfromsample = likelihood(prepped_sample, msmtprepped)
llfromnew = nllnewobject
print(llfromsample - llfromnew)
assert llfromsample - llfromnew < 10
# update sample
if llfromsample - llfromnew < 10:
sample = update(sample, prepped_sample, msmtprepped)
validSample(sample)
assert sample[0] > -5 and sample[0] < 70 and abs(sample[1]) < 50
plotimg = plotImgKitti(view_angle)
# draw object
if havemsmtactually:
box = np.array(gtobj['box'])
addRect2KittiImg(plotimg, box, (0,0,256,1.))
# plot fake measurement
if havemsmt:
box = msmt.copy()#[[1,2,0,3,4]].copy()
addRect2KittiImg(plotimg, box, (0,256*.2,0,.2))
# plot tracked sample
if not samplenotset:
box = sample[:5].copy()
addRect2KittiImg(plotimg, box, (256*.4,0,0,.4))
plotimg = np.minimum((plotimg[:,:,:3]/plotimg[:,:,3:]),255.).astype(np.uint8)
# put the plot on top of the camera image to view, display for 3 seconds
reportedobjects = np.array(reportedobjects).reshape((-1, 5))
reportedscores = np.array(reportedscores)
reportedlabels = np.array(reportedlabels)
metric.add(np.array([gtobj['box'] for gtobj in gt]),
np.array([gtobj['scored'] for gtobj in gt]),
np.array([gtobj['difficulty'] for gtobj in gt]),
reportedobjects, reportedscores)
np.save(
outestimatefiles.format(scene_idx, fileidx),
np.concatenate(
(reportedobjects, reportedscores[:, None], reportedlabels[:,
None]),
axis=1))
# visualize
plotimg1 = plotImgKitti(view_angle)
plotimg2 = plotImgKitti(view_angle)
# shade tiles chosen for detection
for tilex, tiley in np.ndindex(*grndlen):
if not tiles2detectgrid[tilex, tiley] or empty[tilex, tiley]: continue
tilecenterx = (tilex + grndstart[0] + .5) * grndstep[0]
tilecentery = (tiley + grndstart[1] + .5) * grndstep[1]
addRect2KittiImg(plotimg1, (tilecenterx, tilecentery, 0., 1.5, 1.5),
np.array((30., 30., 30., .2)))
# add ground truth
for gtobj in gt:
box = np.array(gtobj['box'])
if gtobj['scored']:
addRect2KittiImg(plotimg1, box, (0, 0, 210 * .9, .9))
else:
addRect2KittiImg(plotimg1, box, (30 * .9, 80 * .9, 255 * .9, .9))
