def get_kinect_transform(robot, sim=False):
"""
Returns transform from base_footprint to camera_depth_optical_frame.
Call update_rave() before this!
"""
if sim:
return tfm_bf_head.dot(tfm_head_dof)
T_w_h = robot.GetLink("head_plate_frame").GetTransform()
T_w_k = T_w_h.dot(tfm_head_dof)
return T_w_k
ar_demo_file = osp.join(hd_data_dir, ar_init_dir, ar_init_demo_name)
with open(ar_demo_file,'r') as fh: ar_demo_tfms = cPickle.load(fh)
# use camera 1 as default
ar_marker_cameras = [1]
ar_demo_tfm = avg_transform([ar_demo_tfms['tfms'][c] for c in ar_demo_tfms['tfms'] if c in ar_marker_cameras])
# Get ar marker for PR2:
# default demo_file
ar_run_file = osp.join(hd_data_dir, ar_init_dir, ar_init_playback_name)
with open(ar_run_file,'r') as fh: ar_run_tfms = cPickle.load(fh)
ar_run_tfm = ar_run_tfms['tfm']
# transform to move the demo points approximately into PR2's frame
# Basically a rough transform from head kinect to demo_camera, given the tables are the same.
init_tfm = ar_run_tfm.dot(np.linalg.inv(ar_demo_tfm))
init_tfm = tfm_bf_head.dot(tfm_head_dof).dot(init_tfm)
seg_info = hdf[demo_name][annotations[0]["name"]]
if ref_image is None:
rgb_image = np.asarray(seg_info["rgb"])
else:
rgb_image = color_match.match(ref_image, np.asarray(seg_info["rgb"]))
#table_cloud0, table_plane0 = cloud_proc_mod.extract_table_ransac(rgb_image, np.asarray(seg_info["depth"]), np.eye(4))
table_cloud, table_plane = cloud_proc_mod.extract_table_pca(rgb_image, np.asarray(seg_info["depth"]), np.eye(4))
if args.offline:
track_video_frames_offline(rgbd_dir, np.eye(4), init_tfm, ref_image, None) #offline
else:
