open3d.ml.torch.datasets.utils.DataProcessing#
- class open3d.ml.torch.datasets.utils.DataProcessing#
- static Acc_from_confusions(confusions)#
- static IoU_from_confusions(confusions)#
Computes IoU from confusion matrices.
- Parameters:
confusions – ([…, n_c, n_c] np.int32). Can be any dimension, the confusion matrices should be described by
the last axes. n_c = number of classes
- Returns:
([…, n_c] np.float32) IoU score
- static cam2img(points, cam_img)#
- static cam2world(points, world_cam)#
- static data_aug(xyz, color, labels, idx, num_out)#
- static get_class_weights(num_per_class)#
- static grid_subsampling(points, features=None, labels=None, grid_size=0.1, verbose=0)#
CPP wrapper for a grid subsampling (method = barycenter for points and features).
- Parameters:
points – (N, 3) matrix of input points
features – optional (N, d) matrix of features (floating number)
labels – optional (N,) matrix of integer labels
grid_size – parameter defining the size of grid voxels
verbose – 1 to display
- Returns:
Subsampled points, with features and/or labels depending of the input
- static invT(T)#
- static knn_search(support_pts, query_pts, k)#
KNN search.
- Parameters:
support_pts – points you have, N1*3
query_pts – points you want to know the neighbour index, N2*3
k – Number of neighbours in knn search
- Returns:
neighboring points indexes, N2*k
- Return type:
neighbor_idx
- static load_label_kitti(label_path, remap_lut)#
- static load_label_semantic3d(filename)#
- static load_pc_kitti(pc_path)#
- static load_pc_semantic3d(filename)#
- static remove_outside_points(points, world_cam, cam_img, image_shape)#
Remove points which are outside of image.
- Parameters:
points (np.ndarray, shape=[N, 3+dims]) – Total points.
world_cam (np.ndarray, shape=[4, 4]) – Matrix to project points in lidar coordinates to camera coordinates.
cam_img (p.array, shape=[4, 4]) – Matrix to project points in camera coordinates to image coordinates.
image_shape (list[int]) – Shape of image.
- Returns:
Filtered points.
- Return type:
np.ndarray, shape=[N, 3+dims]
- static shuffle_idx(x)#
- static shuffle_list(data_list)#
- static world2cam(points, world_cam)#