def read_objects(tracklet_file, frames_index):
objects = [] #grouped by frames
# frames_index = range(15)
for n in frames_index: objects.append([])
# read tracklets from file
tracklets = parseXML(tracklet_file)
num = len(tracklets) #number of obs
for n in range(num):
tracklet = tracklets[n]
# this part is inspired by kitti object development kit matlab code: computeBox3D
h,w,l = tracklet.size
# loop over all data in tracklet
start_frame = tracklet.firstFrame
end_frame=tracklet.firstFrame+tracklet.nFrames
object_in_frames_index = [i for i in frames_index if i in range(start_frame, end_frame)]
object_in_tracklet_index=[i-start_frame for i in object_in_frames_index]
for i in object_in_tracklet_index:
translation = tracklet.trans[i]
rotation = tracklet.rots[i]
state = tracklet.states[i]
occlusion = tracklet.occs[i]
truncation = tracklet.truncs[i]
if cfg.DATA_SETS_TYPE == 'kitti':
# print('truncation filter disable')
# determine if object is in the image; otherwise continue
if truncation not in (TRUNC_IN_IMAGE, TRUNC_TRUNCATED):
continue
# pass
elif cfg.DATA_SETS_TYPE == 'didi2':
# todo : 'truncation filter disable'
pass
elif cfg.DATA_SETS_TYPE == 'didi':
# todo : 'truncation filter disable'
pass
elif cfg.DATA_SETS_TYPE == 'test':
pass
else:
raise ValueError('unexpected type in cfg.DATA_SETS_TYPE :{}!'.format(cfg.DATA_SETS_TYPE))
o = type('', (), {})()
o.type = tracklet.objectType
o.tracklet_id = n
o.translation=translation
o.rotation=rotation
o.size=tracklet.size
objects[frames_index.index(i+start_frame)].append(o)
return objects
def read_objects(tracklet_file, num_frames):
objects = [] #grouped by frames
for n in range(num_frames):
objects.append([])
# read tracklets from file
tracklets = parseXML(tracklet_file)
num = len(tracklets)
for n in range(num):
tracklet = tracklets[n]
# this part is inspired by kitti object development kit matlab code: computeBox3D
h, w, l = tracklet.size
trackletBox = np.array([ # in velodyne coordinates around zero point and without orientation yet\
[-l/2, -l/2, l/2, l/2, -l/2, -l/2, l/2, l/2], \
[ w/2, -w/2, -w/2, w/2, w/2, -w/2, -w/2, w/2], \
[ 0.0, 0.0, 0.0, 0.0, h, h, h, h]])
# loop over all data in tracklet
t = tracklet.firstFrame
#print(tracklet)
#print(type(tracklet))
for translation, rotation, state, occlusion, truncation, amtOcclusion, amtBorders, absoluteFrameNumber in tracklet:
# determine if object is in the image; otherwise continue
if truncation not in (TRUNC_IN_IMAGE, TRUNC_TRUNCATED):
continue
# re-create 3D bounding box in velodyne coordinate system
yaw = rotation[
2] # other rotations are 0 in all xml files I checked
assert np.abs(rotation[:2]).sum(
) == 0, 'object rotations other than yaw given!'
rotMat = np.array([\
[np.cos(yaw), -np.sin(yaw), 0.0], \
[np.sin(yaw), np.cos(yaw), 0.0], \
[ 0.0, 0.0, 1.0]])
cornerPosInVelo = np.dot(rotMat, trackletBox) + np.tile(
translation, (8, 1)).T
# calc yaw as seen from the camera (i.e. 0 degree = facing away from cam), as opposed to
# car-centered yaw (i.e. 0 degree = same orientation as car).
# makes quite a difference for objects in periphery!
# Result is in [0, 2pi]
x, y, z = translation
yawVisual = (yaw - np.arctan2(y, x)) % (2 * math.pi)
o = type('', (), {})()
o.box = cornerPosInVelo.transpose()
o.type = tracklet.objectType
o.tracklet_id = n
objects[t].append(o)
t = t + 1
return objects
def read_objects(tracklet_file):
objects = [] #grouped by frames
# read tracklets from file
tracklets = parseXML(tracklet_file)
num = len(tracklets) #number of obs
objects = [[] for n in range(num)]
for n in range(num):
tracklet = tracklets[n]
# this part is inspired by kitti object development kit matlab code: computeBox3D
h, w, l = tracklet.size
# loop over all data in tracklet
start_frame = tracklet.firstFrame
end_frame = tracklet.firstFrame + tracklet.nFrames
object_in_frames_index = range(start_frame, end_frame)
object_in_tracklet_index = [
i - start_frame for i in object_in_frames_index
]
for i in object_in_tracklet_index:
translation = tracklet.trans[i]
rotation = tracklet.rots[i]
state = tracklet.states[i]
occlusion = tracklet.occs[i]
truncation = tracklet.truncs[i]
if cfg.DATA_SETS_TYPE == 'kitti':
# print('truncation filter disable')
# determine if object is in the image; otherwise continue
if truncation not in (TRUNC_IN_IMAGE, TRUNC_TRUNCATED):
continue
# pass
elif cfg.DATA_SETS_TYPE == 'didi2':
# todo : 'truncation filter disable'
pass
elif cfg.DATA_SETS_TYPE == 'didi':
# todo : 'truncation filter disable'
pass
elif cfg.DATA_SETS_TYPE == 'test':
pass
else:
raise ValueError(
'unexpected type in cfg.DATA_SETS_TYPE :{}!'.format(
cfg.DATA_SETS_TYPE))
o = type('', (), {})()
o.type = tracklet.objectType
o.tracklet_id = n
o.translation = translation
o.rotation = rotation
o.size = tracklet.size
o.start_frame = start_frame
objects[n].append(
(start_frame, translation, rotation, tracklet.size))
return objects
def read_objects(tracklet_file, frames_index):
objects = [] #grouped by frames
# frames_index = range(15)
for n in frames_index:
objects.append([])
# read tracklets from file
tracklets = parseXML(tracklet_file)
num = len(tracklets) #number of obs
for n in range(num):
tracklet = tracklets[n]
# this part is inspired by kitti object development kit matlab code: computeBox3D
h, w, l = tracklet.size
if cfg.DATA_SETS_TYPE == 'didi2' or cfg.DATA_SETS_TYPE == 'didi' or cfg.DATA_SETS_TYPE == 'test':
h, w = h * 1.1, l
trackletBox = np.array([
[-l / 2, -l / 2, l / 2, l / 2, -l / 2, -l / 2, l / 2, l / 2], \
[w / 2, -w / 2, -w / 2, w / 2, w / 2, -w / 2, -w / 2, w / 2], \
[-h/2, -h/2, -h/2, -h/2, h/2, h/2, h/2, h/2]])
elif cfg.DATA_SETS_TYPE == 'kitti':
trackletBox = np.array([ # in velodyne coordinates around zero point and without orientation yet\
[-l / 2, -l / 2, l / 2, l / 2, -l / 2, -l / 2, l / 2, l / 2], \
[w / 2, -w / 2, -w / 2, w / 2, w / 2, -w / 2, -w / 2, w / 2], \
[0.0, 0.0, 0.0, 0.0, h, h, h, h]])
else:
raise ValueError(
'unexpected type in cfg.DATA_SETS_TYPE :{}!'.format(
cfg.DATA_SETS_TYPE))
# loop over all data in tracklet
start_frame = tracklet.firstFrame
end_frame = tracklet.firstFrame + tracklet.nFrames
object_in_frames_index = [
i for i in frames_index if i in range(start_frame, end_frame)
]
object_in_tracklet_index = [
i - start_frame for i in object_in_frames_index
]
for i in object_in_tracklet_index:
translation = tracklet.trans[i]
rotation = tracklet.rots[i]
state = tracklet.states[i]
occlusion = tracklet.occs[i]
truncation = tracklet.truncs[i]
if cfg.DATA_SETS_TYPE == 'kitti':
# print('truncation filter disable')
# determine if object is in the image; otherwise continue
# print (OCC_VISIBLE)
# print (occlusion[1])
# print (TRUNC_IN_IMAGE)
# print (truncation)
if truncation not in (TRUNC_IN_IMAGE, TRUNC_TRUNCATED):
continue
# if (int(truncation),int(occlusion[1])) != (TRUNC_IN_IMAGE, OCC_VISIBLE) :
# continue
# pass
elif cfg.DATA_SETS_TYPE == 'didi2':
# todo : 'truncation filter disable'
pass
elif cfg.DATA_SETS_TYPE == 'didi':
# todo : 'truncation filter disable'
pass
elif cfg.DATA_SETS_TYPE == 'test':
pass
else:
raise ValueError(
'unexpected type in cfg.DATA_SETS_TYPE :{}!'.format(
cfg.DATA_SETS_TYPE))
# re-create 3D bounding box in velodyne coordinate system
yaw = rotation[
2] # other rotations are 0 in all xml files I checked
#assert np.abs(rotation[:2]).sum() == 0, 'object rotations other than yaw given!'
rotMat = np.array([\
[np.cos(yaw), -np.sin(yaw), 0.0], \
[np.sin(yaw), np.cos(yaw), 0.0], \
[ 0.0, 0.0, 1.0]])
cornerPosInVelo = np.dot(rotMat, trackletBox) + np.tile(
translation, (8, 1)).T
# calc yaw as seen from the camera (i.e. 0 degree = facing away from cam), as opposed to
# car-centered yaw (i.e. 0 degree = same orientation as car).
# makes quite a difference for objects in periphery!
# Result is in [0, 2pi]
x, y, z = translation
yawVisual = (yaw - np.arctan2(y, x)) % (2 * math.pi)
o = type('', (), {})()
o.box = cornerPosInVelo.transpose()
o.type = tracklet.objectType
o.tracklet_id = n
if o.type == 'Van' or o.type == 'Truck' or o.type == 'Car' or o.type == 'Tram': # todo : only support 'Van'
o.translation = translation
o.rotation = rotation
o.size = tracklet.size
print('translation')
print(translation)
else:
continue
objects[frames_index.index(i + start_frame)].append(o)
return objects
def read_objects(tracklet_file, frames_index):
objects = [] #grouped by frames
# frames_index = range(15)
for n in frames_index: objects.append([])
# read tracklets from file
tracklets = parseXML(tracklet_file)
num = len(tracklets) #number of obs
for n in range(num):
tracklet = tracklets[n]
# this part is inspired by kitti object development kit matlab code: computeBox3D
h,w,l = tracklet.size
if cfg.DATA_SETS_TYPE == 'didi2' or cfg.DATA_SETS_TYPE == 'didi' or cfg.DATA_SETS_TYPE == 'test':
h, w = h*1.1, l
trackletBox = np.array([
[-l / 2, -l / 2, l / 2, l / 2, -l / 2, -l / 2, l / 2, l / 2], \
[w / 2, -w / 2, -w / 2, w / 2, w / 2, -w / 2, -w / 2, w / 2], \
[-h/2, -h/2, -h/2, -h/2, h/2, h/2, h/2, h/2]])
elif cfg.DATA_SETS_TYPE == 'kitti':
trackletBox = np.array([ # in velodyne coordinates around zero point and without orientation yet\
[-l / 2, -l / 2, l / 2, l / 2, -l / 2, -l / 2, l / 2, l / 2], \
[w / 2, -w / 2, -w / 2, w / 2, w / 2, -w / 2, -w / 2, w / 2], \
[0.0, 0.0, 0.0, 0.0, h, h, h, h]])
else:
raise ValueError('unexpected type in cfg.DATA_SETS_TYPE :{}!'.format(cfg.DATA_SETS_TYPE))
# loop over all data in tracklet
start_frame = tracklet.firstFrame
end_frame=tracklet.firstFrame+tracklet.nFrames
object_in_frames_index = [i for i in frames_index if i in range(start_frame, end_frame)]
object_in_tracklet_index=[i-start_frame for i in object_in_frames_index]
for i in object_in_tracklet_index:
translation = tracklet.trans[i]
rotation = tracklet.rots[i]
state = tracklet.states[i]
occlusion = tracklet.occs[i]
truncation = tracklet.truncs[i]
if cfg.DATA_SETS_TYPE == 'kitti':
# print('truncation filter disable')
# determine if object is in the image; otherwise continue
if truncation not in (TRUNC_IN_IMAGE, TRUNC_TRUNCATED):
continue
# pass
elif cfg.DATA_SETS_TYPE == 'didi2':
# todo : 'truncation filter disable'
pass
elif cfg.DATA_SETS_TYPE == 'didi':
# todo : 'truncation filter disable'
pass
elif cfg.DATA_SETS_TYPE == 'test':
pass
else:
raise ValueError('unexpected type in cfg.DATA_SETS_TYPE :{}!'.format(cfg.DATA_SETS_TYPE))
# re-create 3D bounding box in velodyne coordinate system
yaw = rotation[2] # other rotations are 0 in all xml files I checked
#assert np.abs(rotation[:2]).sum() == 0, 'object rotations other than yaw given!'
rotMat = np.array([\
[np.cos(yaw), -np.sin(yaw), 0.0], \
[np.sin(yaw), np.cos(yaw), 0.0], \
[ 0.0, 0.0, 1.0]])
cornerPosInVelo = np.dot(rotMat, trackletBox) + np.tile(translation, (8,1)).T
# calc yaw as seen from the camera (i.e. 0 degree = facing away from cam), as opposed to
# car-centered yaw (i.e. 0 degree = same orientation as car).
# makes quite a difference for objects in periphery!
# Result is in [0, 2pi]
x, y, z = translation
yawVisual = ( yaw - np.arctan2(y, x) ) % (2*math.pi)
o = type('', (), {})()
o.box = cornerPosInVelo.transpose()
o.type = tracklet.objectType
o.tracklet_id = n
if o.type == 'Van' or o.type == 'Truck' or o.type == 'Car' or o.type == 'Tram': # todo : only support 'Van'
o.translation=translation
o.rotation=rotation
o.size=tracklet.size
else:
continue
objects[frames_index.index(i+start_frame)].append(o)
return objects
