def _get_sym_infos(self, dataset_name):
"""label based keys."""
if dataset_name in self.sym_infos:
return self.sym_infos[dataset_name]
dset_meta = MetadataCatalog.get(dataset_name)
ref_key = dset_meta.ref_key
data_ref = ref.__dict__[ref_key]
objs = dset_meta.objs
cfg = self.cfg
cur_sym_infos = {}
loaded_models_info = data_ref.get_models_info()
for i, obj_name in enumerate(objs):
obj_id = data_ref.obj2id[obj_name]
model_info = loaded_models_info[str(obj_id)]
if "symmetries_discrete" in model_info or "symmetries_continuous" in model_info:
sym_transforms = misc.get_symmetry_transformations(
model_info, max_sym_disc_step=0.01)
sym_info = np.array([sym["R"] for sym in sym_transforms],
dtype=np.float32)
else:
sym_info = None
cur_sym_infos[i] = sym_info
self.sym_infos[dataset_name] = cur_sym_infos
return self.sym_infos[dataset_name]
def get_ycbv_metadata(obj_names, ref_key):
"""task specific metadata."""
data_ref = ref.__dict__[ref_key]
cur_sym_infos = {} # label based key
loaded_models_info = data_ref.get_models_info()
for i, obj_name in enumerate(obj_names):
obj_id = data_ref.obj2id[obj_name]
model_info = loaded_models_info[str(obj_id)]
if "symmetries_discrete" in model_info or "symmetries_continuous" in model_info:
sym_transforms = misc.get_symmetry_transformations(model_info, max_sym_disc_step=0.01)
sym_info = np.array([sym["R"] for sym in sym_transforms], dtype=np.float32)
else:
sym_info = None
cur_sym_infos[i] = sym_info
meta = {"thing_classes": obj_names, "sym_infos": cur_sym_infos}
return meta
# axis_est = np.array([1, 2, 0])
# axis_gt = np.array([0,2,1])
# est_rot = axangle2mat(axis_est, -pi/3)
# gt_rot = axangle2mat(axis_gt, pi)
# sym_info = axangle2mat([0, 0, 1], pi)
# print('sym_info', sym_info)
cls_idx = 3
obj_id = cls_idx - 1
trans = np.array([-0.0021458883, 0.0804758, 0.78142926])
axis_est = np.array([1, 2, 0])
axis_gt = np.array([0, 2, 1])
est_rot = axangle2mat(axis_est, -pi / 3)
gt_rot = axangle2mat(axis_gt, pi)
transforms_sym = get_symmetry_transformations(models_info[cls_idx], max_sym_disc_step=0.01)
# sym_info = axangle2mat([0, 0, 1], pi)
sym_info = np.array([sym["R"] for sym in transforms_sym])
print("sym_info", sym_info.shape)
est_pose = np.random.rand(3, 4)
est_pose[:, :3] = est_rot
gt_pose = np.random.rand(3, 4)
gt_pose[:, :3] = gt_rot
rd_ori = re(est_rot, gt_rot)
t = time.perf_counter()
for i in range(3000):
closest_rot = get_closest_rot(est_rot, gt_rot, sym_info)
print(("calculate closest rot {}s".format((time.perf_counter() - t) / 3000)))
closest_pose = np.copy(gt_pose)
]:
misc.log("Loading object models...")
for obj_id in dp_model["obj_ids"]:
models[obj_id] = inout.load_ply(dp_model["model_tpath"].format(obj_id=obj_id))
# Load models info.
models_info = None
if p["error_type"] in ["ad", "add", "adi", "vsd", "mssd", "mspd", "cus", "reteS", "reS", "teS", "projS"]:
models_info = inout.load_json(dp_model["models_info_path"], keys_to_int=True)
# Get sets of symmetry transformations for the object models.
models_sym = None
if p["error_type"] in ["mssd", "mspd", "reteS", "reS", "teS", "projS"]:
models_sym = {}
for obj_id in dp_model["obj_ids"]:
models_sym[obj_id] = misc.get_symmetry_transformations(models_info[obj_id], p["max_sym_disc_step"])
# Initialize a renderer.
ren = None
if p["error_type"] in ["vsd", "cus"]:
misc.log("Initializing renderer...")
width, height = dp_split["im_size"]
if p["renderer_type"] in ["python", "cpp"]:
ren = renderer.create_renderer(width, height, p["renderer_type"], mode="depth")
for obj_id in dp_model["obj_ids"]:
ren.add_object(obj_id, dp_model["model_tpath"].format(obj_id=obj_id))
elif p["renderer_type"] == "egl":
from lib.egl_renderer.egl_renderer import EGLRenderer
model_paths = [dp_model["model_tpath"].format(obj_id=obj_id) for obj_id in dp_model["obj_ids"]]
texture_paths = [