open3d.ml.tf.ops.nms

open3d.ml.tf.ops.nms(boxes, scores, nms_overlap_thresh, name=None)

Performs non-maximum suppression of bounding boxes and returns the selected box

indices.

# TensorFlow example. import open3d.ml.tf as ml3d import numpy as np

boxes = np.array([[15.0811, -7.9803, 15.6721, -6.8714, 0.5152],

[15.1166, -7.9261, 15.7060, -6.8137, 0.6501], [15.1304, -7.8129, 15.7069, -6.8903, 0.7296], [15.2050, -7.8447, 15.8311, -6.7437, 1.0506], [15.1343, -7.8136, 15.7121, -6.8479, 1.0352], [15.0931, -7.9552, 15.6675, -7.0056, 0.5979]],

dtype=np.float32)

scores = np.array([3, 1.1, 5, 2, 1, 0], dtype=np.float32) nms_overlap_thresh = 0.7 keep_indices = ml3d.ops.nms(boxes, scores, nms_overlap_thresh) print(keep_indices)

# PyTorch example. import torch import open3d.ml.torch as ml3d

boxes = torch.Tensor([[15.0811, -7.9803, 15.6721, -6.8714, 0.5152],

[15.1166, -7.9261, 15.7060, -6.8137, 0.6501], [15.1304, -7.8129, 15.7069, -6.8903, 0.7296], [15.2050, -7.8447, 15.8311, -6.7437, 1.0506], [15.1343, -7.8136, 15.7121, -6.8479, 1.0352], [15.0931, -7.9552, 15.6675, -7.0056, 0.5979]])

scores = torch.Tensor([3, 1.1, 5, 2, 1, 0]) nms_overlap_thresh = 0.7 keep_indices = ml3d.ops.nms(boxes, scores, nms_overlap_thresh) print(keep_indices)

Parameters

• boxes – A Tensor. Must be one of the following types: float32. (N, 5) float32 tensor. Bounding boxes are represented as (x0, y0, x1, y1, rotate).

• scores – A Tensor. Must have the same type as boxes. (N,) float32 tensor. A higher score means a more confident bounding box.

• nms_overlap_thresh –

  A float. float value between 0 and 1. When a high-score box is

  selected, other remaining boxes with IoU > nms_overlap_thresh will be discarded. A higher nms_overlap_thresh means more boxes will be kept.

  returns (M,) int64 tensor. The selected box indices.

• name – A name for the operation (optional).

Returns

A Tensor of type int64.