except TypeError:
mesh, stats_dict = out, {}
time_dict.update(stats_dict)
# Write output
mesh_out_file = os.path.join(mesh_dir, '%s.off' % modelname)
mesh.export(mesh_out_file)
out_file_dict['mesh'] = mesh_out_file
if generate_pointcloud:
t0 = time.time()
pointcloud = generator.generate_pointcloud(data)
time_dict['pcl'] = time.time() - t0
pointcloud_out_file = os.path.join(
pointcloud_dir, '%s.ply' % modelname)
export_pointcloud(pointcloud, pointcloud_out_file)
out_file_dict['pointcloud'] = pointcloud_out_file
if cfg['generation']['copy_input']:
# Save inputs
if input_type == 'pointcloud' or 'partial_pointcloud':
inputs_path = os.path.join(in_dir, '%s.ply' % modelname)
inputs = data['inputs'].squeeze(0).cpu().numpy()
export_pointcloud(inputs, inputs_path, False)
out_file_dict['in'] = inputs_path
# Copy to visualization directory for first vis_n_output samples
c_it = model_counter[category_id]
if c_it < vis_n_outputs:
# Save output files
img_name = '%02d.off' % c_it
mesh = deepcopy(mesh)
mesh.apply_transform(mat_permute)
if save_part_mesh == True:
out_file = join(outfile, 'mesh_fused%d.ply' % idx)
mesh.export(out_file)
if idx == 0:
faces = mesh.faces
vertices = mesh.vertices
print("AAAA")
else:
faces = np.concatenate([faces, mesh.faces + vertices.shape[0]])
vertices = np.concatenate([vertices, mesh.vertices])
print("BBBBB")
mesh = trimesh.Trimesh(vertices=vertices, faces=faces, process=False)
out_file = join(outfile, 'mesh_fused.ply')
mesh.export(out_file)
# Sample surface points
pcl, face_idx = mesh.sample(n_pointcloud_points, return_index=True)
normals = mesh.face_normals[face_idx]
# save surface points
out_file = join(outfile, 'pointcloud.npz')
np.savez(out_file, points=pcl.astype(dtype), normals=normals.astype(dtype))
export_pointcloud(pcl, join(outfile, 'pointcloud.ply'))
# create test.lst file
with open(join(out_path, 'test.lst'), "w") as file:
file.write(scene_name)
pcl_filter = pcl_filter[pcl_filter[:,0] > -1.85]
pcl_filter = pcl_filter[pcl_filter[:,2] > -0.93]
pcl_filter = pcl_filter[pcl_filter[:,2] < 4.85]
plt.hist(pcl_filter[:,2], bins = 90)
plt.show()
#pcd.transform([[1, 0, 0, 0], [0, 0.5, 0.5, 0], [0, -0.5, 0.5, 0], [0, 0, 0, 1]])
from os.path import join, exists, isdir, exists
out_path = 'data/test'
scene_name = 'a'
outfile = join(out_path, scene_name)
out_file = join(outfile, 'pointcloud.npz')
dtype = np.float16
np.savez('pointcloud.npz', points=pcl_filter.astype(dtype), normals=pcl_filter.astype(dtype))
np.savez('pointcloud.npz', points=pcl_filter.astype(dtype))
# save surface points
out_file = join(outfile, 'pointcloud.npz')
np.savez(out_file, points=pcl.astype(dtype), normals=normals.astype(dtype))
export_pointcloud(pcl_filter, 'pointcloud_align.ply')
export_pointcloud(pcl_filter, 'pointcloud_align_filter.ply')
####### Try create occlusion ######