def translate_z_neg(vis):
global CURRENT_INDEX, offset
translation = c3D.makeTranslation4x4(np.asarray([0., 0., -offset]))
pcd_list[CURRENT_INDEX].transform(translation)
vis.update_geometry(pcd_list[CURRENT_INDEX])
all_transformations[CURRENT_INDEX][0:3, 3] = translation[
0:3, 3] + all_transformations[CURRENT_INDEX][0:3, 3]
cloud_m = o3.read_point_cloud(args.model)
""" if you use object model with meter scale, try this code to convert meter scale."""
#cloud_m = c3D.Scaling( cloud_m, 0.001 )
cloud_m_ds = o3.voxel_down_sample(cloud_m, voxel_size)
"""Loading of the initial transformation"""
initial_trans = np.identity(4)
if os.path.exists(args.init):
initial_trans = c3D.load_transformation(args.init)
print('Use initial transformation\n', initial_trans)
all_transformation = np.dot(initial_trans, all_transformation)
else:
# if initial transformation is not avairable,
# the object model is moved to its center.
cloud_m_c, offset = c3D.Centering(cloud_m_ds)
mat_centering = c3D.makeTranslation4x4(-1.0 * offset)
all_transformation = np.dot(mat_centering, all_transformation)
CLOUD_ROT = copy.deepcopy(cloud_m_ds)
CLOUD_ROT.transform(all_transformation)
mapping = Mapping('./data/realsense_intrinsic.json')
img_mapped = mapping.Cloud2Image(CLOUD_ROT)
"""Mouse event"""
window_name = '6DoF Pose Annotator'
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
cv2.setMouseCallback(window_name, mouse_event,
[window_name, im_color, im_depth, mapping])
generateImage(mapping, im_color)
while (True):
global all_pcd_list
for path in gt_paths:
all_pcd_list.append(o3d.io.read_triangle_mesh(path))
all_pcd_list = []
load_gt_meshes(obj_gt_paths)
# Object parameters
CURRENT_INDEX = 0
MAX_OBJ = len(obj_gt_paths)
# Annotation parameters
offset = 0.01
rot_step = 0.1 * np.pi
all_transformations = [c3D.makeTranslation4x4([0, 0, 0]) for _ in obj_gt_paths]
# pipline parameters
seq = 0
step = -1
path = './data/'
scene_mesh = None
visible_objects = True
view_size = 2.
view_bounds = np.array([view_size] * 3)
# Load scene data
def load_step_data(path, seq, step, real_data=False):
if not real_data: