def database_delete_grasps(self, object_name):
# load gripper
gripper = RobotGripper.load(GRIPPER_NAME, gripper_dir='/home/silvia/dex-net/data/grippers')
# open Dex-Net API
dexnet_handle = DexNet()
dexnet_handle.open_database(self.database_path)
dexnet_handle.open_dataset(self.dataset_name)
dexnet_handle.dataset.delete_grasps(object_name, gripper=gripper.name)
dexnet_handle.close_database()
def get_stable_pose_transform(self, object_name, stable_pose_id):
# load gripper
gripper = RobotGripper.load(
GRIPPER_NAME, gripper_dir='/home/silvia/dex-net/data/grippers')
# open Dex-Net API
dexnet_handle = DexNet()
dexnet_handle.open_database(self.database_path)
dexnet_handle.open_dataset(self.dataset_name)
stable_pose = dexnet_handle.dataset.stable_pose(
object_name, stable_pose_id=('pose_' + str(stable_pose_id)))
dexnet_handle.close_database()
return stable_pose
def database_save(self, object_name, filepath, stable_poses_n, force_overwrite=False):
# load gripper
gripper = RobotGripper.load(GRIPPER_NAME, gripper_dir='/home/silvia/dex-net/data/grippers')
# open Dex-Net API
dexnet_handle = DexNet()
dexnet_handle.open_database(self.database_path)
dexnet_handle.open_dataset(self.dataset_name)
mass = CONFIG['default_mass']
if object_name in dexnet_handle.dataset.object_keys:
graspable = dexnet_handle.dataset[object_name]
mesh = graspable.mesh
sdf = graspable.sdf
stable_poses = dexnet_handle.dataset.stable_poses(object_name)
else:
# Create temp dir if cache dir is not provided
mp_cache = CONFIG['cache_dir']
del_cache = False
if mp_cache is None:
mp_cache = tempfile.mkdtemp()
del_cache = True
# open mesh preprocessor
mesh_processor = MeshProcessor(filepath, mp_cache)
mesh_processor.generate_graspable(CONFIG)
mesh = mesh_processor.mesh
sdf = mesh_processor.sdf
stable_poses = mesh_processor.stable_poses[:stable_poses_n]
# write graspable to database
dexnet_handle.dataset.create_graspable(object_name, mesh, sdf, stable_poses, mass=mass)
# write grasps to database
grasps, metrics = antipodal_grasp_sampler_for_storing(mesh, sdf, stable_poses)
id = 0
for grasps_for_pose, metrics_for_pose in zip(grasps, metrics):
if (grasps_for_pose == None):
continue
dexnet_handle.dataset.store_grasps_and_metrics(object_name, grasps_for_pose, metrics_for_pose,
gripper=gripper.name, stable_pose_id=('pose_'+str(id)),
force_overwrite=force_overwrite)
id = id + 1
dexnet_handle.close_database()
def delete_graspable(self, object_name):
# open Dex-Net API
dexnet_handle = DexNet()
dexnet_handle.open_database(self.database_path)
dexnet_handle.open_dataset(self.dataset_name)
dexnet_handle.dataset.delete_graspable(object_name)
# delete files related to object
path_to_obj_file = ".dexnet/" + object_name
if os.path.exists(path_to_obj_file + "_proc.sdf"):
print("sdf file removed")
os.remove(path_to_obj_file + "_proc.sdf")
if os.path.exists(path_to_obj_file + "_proc.obj"):
print("obj file removed")
os.remove(path_to_obj_file + "_proc.obj")
dexnet_handle.close_database()
def get_stable_pose(self, object_name, stable_pose_id):
# load gripper
gripper = RobotGripper.load(GRIPPER_NAME, gripper_dir='/home/silvia/dex-net/data/grippers')
# open Dex-Net API
dexnet_handle = DexNet()
dexnet_handle.open_database(self.database_path)
dexnet_handle.open_dataset(self.dataset_name)
# read the most robust grasp
stable_pose = dexnet_handle.dataset.stable_pose(object_name, stable_pose_id=('pose_'+str(stable_pose_id)))
dexnet_handle.close_database()
pose_matrix = np.eye(4,4)
pose_matrix[:3,:3] = stable_pose.T_obj_world.rotation
pose_matrix[:3, 3] = stable_pose.T_obj_world.translation
return pose_matrix
def database_save(self,
object_name,
filepath,
stable_poses_n,
metric,
overwrite_object=False,
force_overwrite=False):
# load gripper
gripper = RobotGripper.load(
GRIPPER_NAME, gripper_dir='/home/silvia/dex-net/data/grippers')
# open Dex-Net API
dexnet_handle = DexNet()
dexnet_handle.open_database(self.database_path)
dexnet_handle.open_dataset(self.dataset_name)
mass = CONFIG['default_mass']
if object_name in dexnet_handle.dataset.object_keys:
if not overwrite_object:
dexnet_handle.close_database()
print(object_name +
" already exists in database, not overwriting")
return
graspable = dexnet_handle.dataset[object_name]
mesh = graspable.mesh
sdf = graspable.sdf
stable_poses = dexnet_handle.dataset.stable_poses(object_name)
else:
# Create temp dir if cache dir is not provided
mp_cache = CONFIG['cache_dir']
del_cache = False
if mp_cache is None:
mp_cache = tempfile.mkdtemp()
del_cache = True
# open mesh preprocessor
graspable = MeshProcessor(filepath, mp_cache)
graspable.generate_graspable(CONFIG)
mesh = graspable.mesh
sdf = graspable.sdf
stable_poses = graspable.stable_poses[:stable_poses_n]
# write graspable to database
dexnet_handle.dataset.create_graspable(object_name,
mesh,
sdf,
stable_poses,
mass=mass)
if force_overwrite:
dexnet_handle.dataset.delete_grasps(object_name,
gripper=gripper.name)
# calculate or retrieve grasps
loaded_grasps = dexnet_handle.dataset.grasps(object_name,
gripper=gripper.name)
if loaded_grasps == []:
print("No grasps in database, calculating")
grasps = antipodal_grasp_sampler_for_storing(graspable)
if (grasps != None):
print("Saving grasps")
dexnet_handle.dataset.store_grasps(
object_name,
grasps,
gripper=gripper.name,
force_overwrite=force_overwrite)
loaded_grasps = dexnet_handle.dataset.grasps(
object_name, gripper=gripper.name)
print("Calculating grasp quality")
metrics = grasp_quality_calculator(mesh, sdf, loaded_grasps, metric)
print("Grasp quality calculated")
grasp_metrics = {}
for g in loaded_grasps:
grasp_metrics[g.id] = {}
grasp_metrics[g.id][metric] = metrics[g.id]
dexnet_handle.dataset.store_grasp_metrics(object_name,
grasp_metrics,
gripper=gripper.name)
dexnet_handle.close_database()