def load_bop(bop_dataset_path: str, sys_paths: Union[List[str], str], temp_dir: str = None, model_type: str = "", cam_type: str = "", split: str = "test", scene_id: int = -1, obj_ids: list = [], sample_objects: bool = False, num_of_objs_to_sample: int = None, obj_instances_limit: int = -1, move_origin_to_x_y_plane: bool = False, source_frame: list = ["X", "-Y", "-Z"], mm2m: bool = False) -> List[MeshObject]:
""" Loads the 3D models of any BOP dataset and allows replicating BOP scenes
- Interfaces with the bob_toolkit, allows loading of train, val and test splits
- Relative camera poses are loaded/computed with respect to a reference model
- Sets real camera intrinsics
:param bop_dataset_path: Full path to a specific bop dataset e.g. /home/user/bop/tless.
:param sys_paths: System paths to append. Can be a string or a list of strings.
:param temp_dir: A temp directory which is used for writing the temporary .ply file.
:param model_type: Optionally, specify type of BOP model. Available: [reconst, cad or eval].
:param cam_type: Camera type. If not defined, dataset-specific default camera type is used.
:param split: Optionally, test or val split depending on BOP dataset.
:param scene_id: Optionally, specify BOP dataset scene to synthetically replicate. Default: -1 (no scene is replicated,
only BOP Objects are loaded).
:param obj_ids: List of object ids to load. Default: [] (all objects from the given BOP dataset if scene_id is not
specified).
:param sample_objects: Toggles object sampling from the specified dataset.
:param num_of_objs_to_sample: Amount of objects to sample from the specified dataset. If this amount is bigger than the dataset
actually contains, then all objects will be loaded.
:param obj_instances_limit: Limits the amount of object copies when sampling. Default: -1 (no limit).
:param move_origin_to_x_y_plane: Move center of the object to the lower side of the object, this will not work when used in combination with
pose estimation tasks! This is designed for the use-case where BOP objects are used as filler objects in
the background.
:param source_frame: Can be used if the given positions and rotations are specified in frames different from the blender
frame. Has to be a list of three strings. Example: ['X', '-Z', 'Y']: Point (1,2,3) will be transformed
to (1, -3, 2). Available: ['X', 'Y', 'Z', '-X', '-Y', '-Z'].
:param mm2m: Specify whether to convert poses and models to meters.
:return: The list of loaded mesh objects.
"""
# Make sure sys_paths is a list
if not isinstance(sys_paths, list):
sys_paths = [sys_paths]
for sys_path in sys_paths:
if 'bop_toolkit' in sys_path:
sys.path.append(sys_path)
if temp_dir is None:
temp_dir = Utility.get_temporary_directory()
scale = 0.001 if mm2m else 1
bop_dataset_name = os.path.basename(bop_dataset_path)
has_external_texture = bop_dataset_name in ["ycbv", "ruapc"]
if obj_ids or sample_objects:
allow_duplication = True
else:
allow_duplication = False
datasets_path = os.path.dirname(bop_dataset_path)
dataset = os.path.basename(bop_dataset_path)
print("bob: {}, dataset_path: {}".format(bop_dataset_path, datasets_path))
print("dataset: {}".format(dataset))
try:
from bop_toolkit_lib import dataset_params, inout
except ImportError as error:
print('ERROR: Please download the bop_toolkit package and add it to sys_paths in config!')
print('https://github.com/thodan/bop_toolkit')
raise error
model_p = dataset_params.get_model_params(datasets_path, dataset, model_type=model_type if model_type else None)
cam_p = dataset_params.get_camera_params(datasets_path, dataset, cam_type=cam_type if cam_type else None)
try:
split_p = dataset_params.get_split_params(datasets_path, dataset, split=split)
except ValueError:
raise Exception("Wrong path or {} split does not exist in {}.".format(split, dataset))
bpy.context.scene.render.resolution_x = cam_p['im_size'][0]
bpy.context.scene.render.resolution_y = cam_p['im_size'][1]
loaded_objects = []
# only load all/selected objects here, use other modules for setting poses
# e.g. camera.CameraSampler / object.ObjectPoseSampler
if scene_id == -1:
# TLESS exception because images are cropped
if bop_dataset_name in ['tless']:
cam_p['K'][0, 2] = split_p['im_size'][0] / 2
cam_p['K'][1, 2] = split_p['im_size'][1] / 2
# set camera intrinsics
CameraUtility.set_intrinsics_from_K_matrix(cam_p['K'], split_p['im_size'][0], split_p['im_size'][1])
obj_ids = obj_ids if obj_ids else model_p['obj_ids']
# if sampling is enabled
if sample_objects:
loaded_ids = {}
loaded_amount = 0
if obj_instances_limit != -1 and len(obj_ids) * obj_instances_limit < num_of_objs_to_sample:
raise RuntimeError("{}'s {} split contains {} objects, {} object where requested to sample with "
"an instances limit of {}. Raise the limit amount or decrease the requested "
"amount of objects.".format(bop_dataset_path, split, len(obj_ids),
num_of_objs_to_sample,
obj_instances_limit))
while loaded_amount != num_of_objs_to_sample:
random_id = choice(obj_ids)
if random_id not in loaded_ids.keys():
loaded_ids.update({random_id: 0})
# if there is no limit or if there is one, but it is not reached for this particular object
if obj_instances_limit == -1 or loaded_ids[random_id] < obj_instances_limit:
cur_obj = BopLoader._load_mesh(random_id, model_p, bop_dataset_name, has_external_texture, temp_dir, allow_duplication, scale)
loaded_ids[random_id] += 1
loaded_amount += 1
loaded_objects.append(cur_obj)
else:
print("ID {} was loaded {} times with limit of {}. Total loaded amount {} while {} are "
"being requested".format(random_id, loaded_ids[random_id], obj_instances_limit,
loaded_amount, num_of_objs_to_sample))
else:
for obj_id in obj_ids:
cur_obj = BopLoader._load_mesh(obj_id, model_p, bop_dataset_name, has_external_texture, temp_dir, allow_duplication, scale)
loaded_objects.append(cur_obj)
# replicate scene: load scene objects, object poses, camera intrinsics and camera poses
else:
sc_gt = inout.load_scene_gt(split_p['scene_gt_tpath'].format(**{'scene_id': scene_id}))
sc_camera = inout.load_json(split_p['scene_camera_tpath'].format(**{'scene_id': scene_id}))
for i, (cam_id, insts) in enumerate(sc_gt.items()):
cam_K, cam_H_m2c_ref = BopLoader._get_ref_cam_extrinsics_intrinsics(sc_camera, cam_id, insts, scale)
if i == 0:
# define world = first camera
cam_H_m2w_ref = cam_H_m2c_ref.copy()
cur_objs = []
# load scene objects and set their poses
for inst in insts:
cur_objs.append(BopLoader._load_mesh(inst['obj_id'], model_p, bop_dataset_name, has_external_texture, temp_dir, allow_duplication, scale))
BopLoader.set_object_pose(cur_objs[-1], inst, scale)
cam_H_c2w = BopLoader._compute_camera_to_world_trafo(cam_H_m2w_ref, cam_H_m2c_ref, source_frame)
# set camera intrinsics
CameraUtility.set_intrinsics_from_K_matrix(cam_K, split_p['im_size'][0], split_p['im_size'][1])
# set camera extrinsics as next frame
frame_id = CameraUtility.add_camera_pose(cam_H_c2w)
# Add key frame for camera shift, as it changes from frame to frame in the tless replication
cam = bpy.context.scene.camera.data
cam.keyframe_insert(data_path='shift_x', frame=frame_id)
cam.keyframe_insert(data_path='shift_y', frame=frame_id)
# Copy object poses to key frame (to be sure)
for cur_obj in cur_objs:
BopLoader._insert_key_frames(cur_obj, frame_id)
# move the origin of the object to the world origin and on top of the X-Y plane
# makes it easier to place them later on, this does not change the `.location`
# This is only useful if the BOP objects are not used in a pose estimation scenario.
if move_origin_to_x_y_plane:
for obj in loaded_objects:
obj.move_origin_to_bottom_mean_point()
return loaded_objects
def _set_cam_intrinsics(self, cam, config):
""" Sets camera intrinsics from a source with following priority
1. from config function parameter if defined
2. from custom properties of cam if set in Loader
3. default config:
resolution_x/y: 512
pixel_aspect_x: 1
clip_start: : 0.1
clip_end : 1000
fov : 0.691111
:param cam: The camera which contains only camera specific attributes.
:param config: A configuration object with cam intrinsics.
"""
if config.is_empty():
return
width = config.get_int("resolution_x",
bpy.context.scene.render.resolution_x)
height = config.get_int("resolution_y",
bpy.context.scene.render.resolution_y)
# Clipping
clip_start = config.get_float("clip_start", cam.clip_start)
clip_end = config.get_float("clip_end", cam.clip_end)
if config.has_param("cam_K"):
if config.has_param("fov"):
print(
'WARNING: FOV defined in config is ignored. Mutually exclusive with cam_K'
)
if config.has_param("pixel_aspect_x"):
print(
'WARNING: pixel_aspect_x defined in config is ignored. Mutually exclusive with cam_K'
)
cam_K = np.array(config.get_list("cam_K")).reshape(3, 3).astype(
np.float32)
CameraUtility.set_intrinsics_from_K_matrix(cam_K, width, height,
clip_start, clip_end)
else:
# Set FOV
fov = config.get_float("fov", cam.angle)
# Set Pixel Aspect Ratio
pixel_aspect_x = config.get_float(
"pixel_aspect_x", bpy.context.scene.render.pixel_aspect_x)
pixel_aspect_y = config.get_float(
"pixel_aspect_y", bpy.context.scene.render.pixel_aspect_y)
# Set camera shift
shift_x = config.get_float("shift_x", cam.shift_x)
shift_y = config.get_float("shift_y", cam.shift_y)
CameraUtility.set_intrinsics_from_blender_params(fov,
width,
height,
clip_start,
clip_end,
pixel_aspect_x,
pixel_aspect_y,
shift_x,
shift_y,
lens_unit="FOV")
CameraUtility.set_stereo_parameters(
config.get_string("stereo_convergence_mode",
cam.stereo.convergence_mode),
config.get_float("convergence_distance",
cam.stereo.convergence_distance),
config.get_float("interocular_distance",
cam.stereo.interocular_distance))
if config.has_param("depth_of_field"):
depth_of_field_config = Config(
config.get_raw_dict("depth_of_field"))
fstop_value = depth_of_field_config.get_float("fstop", 2.4)
aperture_blades = depth_of_field_config.get_int(
"aperture_blades", 0)
aperture_ratio = depth_of_field_config.get_float(
"aperture_ratio", 1.0)
aperture_rotation = depth_of_field_config.get_float(
"aperture_rotation_in_rad", 0.0)
if depth_of_field_config.has_param(
"depth_of_field_dist") and depth_of_field_config.has_param(
"focal_object"):
raise RuntimeError(
"You can only use either depth_of_field_dist or a focal_object but not both!"
)
if depth_of_field_config.has_param("depth_of_field_dist"):
depth_of_field_dist = depth_of_field_config.get_float(
"depth_of_field_dist")
CameraUtility.add_depth_of_field(cam, None, fstop_value,
aperture_blades,
aperture_rotation,
aperture_ratio,
depth_of_field_dist)
elif depth_of_field_config.has_param("focal_object"):
focal_object = depth_of_field_config.get_list("focal_object")
if len(focal_object) != 1:
raise RuntimeError(
f"There has to be exactly one focal object, use 'random_samples: 1' or change "
f"the selector. Found {len(focal_object)}.")
CameraUtility.add_depth_of_field(Entity(focal_object[0]),
fstop_value, aperture_blades,
aperture_rotation,
aperture_ratio)
else:
raise RuntimeError(
"The depth_of_field dict must contain either a focal_object definition or "
"a depth_of_field_dist")