def iterframes(self, *args, **kwargs):
for (left, right), oxts, velodyne in izip(
self.iter_stereo_frames(*args, **kwargs),
self.iter_oxts_frames(*args, **kwargs),
self.iter_velodyne_frames(*args, **kwargs)):
yield AttrDict(left=left, right=right, velodyne=velodyne,
pose=oxts.pose, oxts=oxts.packet)
def itervalues_for_keys(self, keys, inds=None, verbose=False):
for key in keys:
if key not in self.keys:
raise RuntimeError(
'Key %s not found in dataset. keys: %s' % (key, self.keys))
items = (self.itervalues_for_key(key) for key in keys)
return izip(*items)
def iterchunks_keys(self, keys, batch_size=10, verbose=False):
"""
Iterate in chunks and izip specific keys
"""
for key in keys:
if key not in self.keys_:
raise RuntimeError(
'Key %s not found in dataset. keys: %s' % (key, self.keys_))
iterables = [self.iterchunks(
key, batch_size=batch_size, verbose=verbose) for key in keys]
return izip(*iterables)
def iter_gt_frames(self, *args, **kwargs):
"""
Iterate over all the ground-truth data
- For noc, occ disparity conversion, see
devkit_stereo_flow/matlab/disp_read.m
"""
for (left, right), noc, occ, calib in izip(
self.iter_stereo_frames(*args, **kwargs),
self.noc.iteritems(*args, **kwargs),
self.occ.iteritems(*args, **kwargs),
self.calib.iteritems(*args, **kwargs)):
yield AttrDict(left=left, right=right,
depth=(occ/256).astype(np.float32),
noc=(noc/256).astype(np.float32),
occ=(occ/256).astype(np.float32),
calib=calib, pose=None)
def iter_keys_values(self, keys, inds=None, verbose=False):
for key in keys:
if key not in self.keys_:
raise RuntimeError(
'Key %s not found in dataset. keys: %s' % (key, self.keys_))
idx, ii = 0, 0
total_chunks = len(self.meta_file_.chunks)
inds = np.sort(inds) if inds is not None else None
for chunk_idx, chunk in enumerate(self.meta_file_.chunks):
data = AttrDict.load(self.get_chunk_filename(chunk_idx))
# if inds is None:
items = (data[key] for key in keys)
for item in izip(*items):
yield item
def iter_stereo_velodyne_frames(self, *args, **kwargs):
return izip(self.left.iteritems(*args, **kwargs),
self.right.iteritems(*args, **kwargs),
self.velodyne.iteritems(*args, **kwargs))
def iterframes(self, *args, **kwargs):
for (left, right), pose in izip(
self.iter_stereo_frames(*args, **kwargs),
self.poses.iteritems(*args, **kwargs)):
yield AttrDict(left=left, right=right,
velodyne=None, pose=pose)
def iteritems(self, *args, **kwargs):
return izip(self.left.iteritems(*args, **kwargs),
self.right.iteritems(*args, **kwargs))
def publish_point_type(pub_channel,
_arr,
c='r',
point_type='POINT',
flip_rb=False,
frame_id='camera',
element_id=0,
reset=True):
"""
Publish point cloud on:
pub_channel: Channel on which the cloud will be published
arr: numpy array (N x 3) for point cloud data
c: Option 1: 'c', 'b', 'r' etc colors accepted by matplotlibs color
Option 2: float ranging from 0 to 1 via matplotlib's jet colormap
Option 3: numpy array (N x 3) with r,g,b vals ranging from 0 to 1
s: supported only by matplotlib plotting
alpha: supported only by matplotlib plotting
Supports
POINT=1, LINE_STRIP=2, LINE_LOOP=3, LINES=4,
TRIANGLE_STRIP=5, TRIANGLE_FAN=6, TRIANGLES=7,
QUAD_STRIP=8, QUADS=9, POLYGON=10
"""
global g_viz_pub
# point3d list collection msg
pc_list_msg = vs.point3d_list_collection_t()
pc_list_msg.id = g_viz_pub.channel_uid(pub_channel)
pc_list_msg.name = pub_channel
pc_list_msg.type = getattr(vs.point3d_list_collection_t, point_type)
pc_list_msg.reset = reset
# pc_list_msg.point_lists = []
# Create the point cloud msg
if isinstance(_arr, list) or isinstance(_arr, deque):
element_ids = element_id if isinstance(element_id,
list) else [0] * len(_arr)
# print 'Multiple elements: ', element_ids
assert (len(c) == len(_arr))
for element_id, _arr_item, _carr_item in izip(element_ids, _arr, c):
arr, carr = copy_pointcloud_data(_arr_item,
_carr_item,
flip_rb=flip_rb)
pc_msg = arr_msg(arr,
carr=carr,
frame_uid=g_viz_pub.channel_uid(frame_id),
element_id=element_id)
pc_list_msg.point_lists.extend([pc_msg])
else:
# print 'Single element: ', element_id
arr, carr = copy_pointcloud_data(_arr, c, flip_rb=flip_rb)
pc_msg = arr_msg(arr,
carr=carr,
frame_uid=g_viz_pub.channel_uid(frame_id),
element_id=element_id)
pc_list_msg.point_lists.extend([pc_msg])
# add to point cloud list
# print('published %i lists %s' % (len(_arr), reset))
pc_list_msg.nlists = len(pc_list_msg.point_lists)
g_viz_pub.publish("POINTS_COLLECTION", serialize(pc_list_msg))
