class MeshRendering:
def __init__(self, json_file, depth_image=False):
with open(json_file, 'r') as fin:
json_dict = json.load(fin)
self.camera = PinholeCamera()
self.rotations = np.array(json_dict['rotations'])
print('\tTotal #view={}'.format(self.rotations.shape[0]))
self.mesh_files = json_dict['mesh_files']
print('\tTotal #mesh={}'.format(len(self.mesh_files)))
self.mat_file_paths = json_dict['mat_file_paths']
self.depth_image = depth_image
if json_dict.get('meshv_attr_dict', None) is not None:
self.meshv_attr_dict = json_dict['meshv_attr_dict']
if json_dict.get('meshv_list_attr_dict', None) is not None:
self.meshv_list_attr_dict = json_dict['meshv_list_attr_dict']
#else:
# if json_dict.get('correspondence_files', None) is not None:
# self.meshv_attr_dict = { 'correspondence': [] }
def render(self, offset, length):
for mesh_id in range(offset, offset + length):
print('mesh id = {}'.format(mesh_id))
mesh_file = self.mesh_files[mesh_id]
mat_file_path = self.mat_file_paths[mesh_id]
mesh = o3d.io.read_triangle_mesh(mesh_file)
os.system('mkdir -p {}'.format(osp.dirname(mat_file_path)))
for view_id, rotation in enumerate(self.rotations):
transformation = np.eye(4)
transformation[:3, :3] = rotation
mesh.transform(transformation)
packed = self.camera.project(mesh.vertices, mesh.triangles)
depth_image, extrinsic, intrinsic = packed[0], packed[
1], packed[2]
points3d_i, correspondence, valid_idx = packed[3], packed[
4], packed[5]
mesh.transform(transformation.T)
output_dict = {}
if self.depth_image:
depth = depth_image[(valid_idx[:, 0], valid_idx[:, 1])]
output_dict['depth'] = depth
output_dict['valid_pixel_indices'] = valid_idx
output_dict['width'] = 320
output_dict['height'] = 240
output_dict['points3d'] = points3d_i
#output_dict['correspondence'] = gt_correspondence
for name, attr in self.meshv_attr_dict.items():
output_dict[name] = np.array(attr)[correspondence]
for name, attr in self.meshv_list_attr_dict.items():
output_dict[name] = np.array(attr[mesh_id])[correspondence]
output_dict['mesh_correspondence'] = correspondence
output_dict['rotation'] = rotation
output_dict['intrinsic'] = intrinsic
output_dict['extrinsic'] = extrinsic
mat_file = mat_file_path.format(view_id)
print('saving to %s' % mat_file)
sio.savemat(mat_file, output_dict, do_compression=True)
depths = []
points3d = []
valid_pixel_indices = []
correspondences = []
intrinsics = []
extrinsics = []
gt_feats = []
gt_correspondences = []
current = 0
used_rotations = []
for i, rotation in enumerate(rotations):
transformation = np.eye(4)
transformation[:3, :3] = rotation
mesh.transform(transformation)
depth_image, extrinsic, intrinsic, points3d_i, correspondence, valid_idx = camera.project(
mesh.vertices, mesh.triangles)
mesh.transform(transformation.T)
depth = depth_image[(valid_idx[:, 0], valid_idx[:, 1])]
helper.save_to_obj(OBJ.format(scan_id, i),
vis.getPointCloud(points3d_i))
gt_correspondence = smpl_corres[correspondence]
np.savetxt(CORRES.format(scan_id, i), gt_correspondence, '%d')
mat_file = MAT.format(scan_id, i)
print('saving to %s' % mat_file)
sio.savemat(mat_file, {
'depth': depth,
'points3d': points3d_i,
'valid_pixel_indices': valid_idx,
'correspondence': gt_correspondence,
'mesh_correspondence': correspondence,
'rotation': rotation,