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| # Copyright (c) Facebook, Inc. and its affiliates. | |
| from __future__ import absolute_import, division, print_function, unicode_literals | |
| import numpy as np | |
| import unittest | |
| from copy import deepcopy | |
| import torch | |
| from torchvision import ops | |
| from detectron2.layers import batched_nms, batched_nms_rotated, nms_rotated | |
| from detectron2.utils.testing import random_boxes | |
| def nms_edit_distance(keep1, keep2): | |
| """ | |
| Compare the "keep" result of two nms call. | |
| They are allowed to be different in terms of edit distance | |
| due to floating point precision issues, e.g., | |
| if a box happen to have an IoU of 0.5 with another box, | |
| one implentation may choose to keep it while another may discard it. | |
| """ | |
| keep1, keep2 = keep1.cpu(), keep2.cpu() | |
| if torch.equal(keep1, keep2): | |
| # they should be equal most of the time | |
| return 0 | |
| keep1, keep2 = tuple(keep1), tuple(keep2) | |
| m, n = len(keep1), len(keep2) | |
| # edit distance with DP | |
| f = [np.arange(n + 1), np.arange(n + 1)] | |
| for i in range(m): | |
| cur_row = i % 2 | |
| other_row = (i + 1) % 2 | |
| f[other_row][0] = i + 1 | |
| for j in range(n): | |
| f[other_row][j + 1] = ( | |
| f[cur_row][j] | |
| if keep1[i] == keep2[j] | |
| else min(min(f[cur_row][j], f[cur_row][j + 1]), f[other_row][j]) + 1 | |
| ) | |
| return f[m % 2][n] | |
| class TestNMSRotated(unittest.TestCase): | |
| def reference_horizontal_nms(self, boxes, scores, iou_threshold): | |
| """ | |
| Args: | |
| box_scores (N, 5): boxes in corner-form and probabilities. | |
| (Note here 5 == 4 + 1, i.e., 4-dim horizontal box + 1-dim prob) | |
| iou_threshold: intersection over union threshold. | |
| Returns: | |
| picked: a list of indexes of the kept boxes | |
| """ | |
| picked = [] | |
| _, indexes = scores.sort(descending=True) | |
| while len(indexes) > 0: | |
| current = indexes[0] | |
| picked.append(current.item()) | |
| if len(indexes) == 1: | |
| break | |
| current_box = boxes[current, :] | |
| indexes = indexes[1:] | |
| rest_boxes = boxes[indexes, :] | |
| iou = ops.box_iou(rest_boxes, current_box.unsqueeze(0)).squeeze(1) | |
| indexes = indexes[iou <= iou_threshold] | |
| return torch.as_tensor(picked) | |
| def _create_tensors(self, N, device="cpu"): | |
| boxes = random_boxes(N, 200, device=device) | |
| scores = torch.rand(N, device=device) | |
| return boxes, scores | |
| def test_batched_nms_rotated_0_degree_cpu(self, device="cpu"): | |
| N = 2000 | |
| num_classes = 50 | |
| boxes, scores = self._create_tensors(N, device=device) | |
| idxs = torch.randint(0, num_classes, (N,)) | |
| rotated_boxes = torch.zeros(N, 5, device=device) | |
| rotated_boxes[:, 0] = (boxes[:, 0] + boxes[:, 2]) / 2.0 | |
| rotated_boxes[:, 1] = (boxes[:, 1] + boxes[:, 3]) / 2.0 | |
| rotated_boxes[:, 2] = boxes[:, 2] - boxes[:, 0] | |
| rotated_boxes[:, 3] = boxes[:, 3] - boxes[:, 1] | |
| err_msg = "Rotated NMS with 0 degree is incompatible with horizontal NMS for IoU={}" | |
| for iou in [0.2, 0.5, 0.8]: | |
| backup = boxes.clone() | |
| keep_ref = batched_nms(boxes, scores, idxs, iou) | |
| assert torch.allclose(boxes, backup), "boxes modified by batched_nms" | |
| backup = rotated_boxes.clone() | |
| keep = batched_nms_rotated(rotated_boxes, scores, idxs, iou) | |
| assert torch.allclose( | |
| rotated_boxes, backup | |
| ), "rotated_boxes modified by batched_nms_rotated" | |
| # Occasionally the gap can be large if there are many IOU on the threshold boundary | |
| self.assertLessEqual(nms_edit_distance(keep, keep_ref), 5, err_msg.format(iou)) | |
| def test_batched_nms_rotated_0_degree_cuda(self): | |
| self.test_batched_nms_rotated_0_degree_cpu(device="cuda") | |
| def test_nms_rotated_0_degree_cpu(self, device="cpu"): | |
| N = 1000 | |
| boxes, scores = self._create_tensors(N, device=device) | |
| rotated_boxes = torch.zeros(N, 5, device=device) | |
| rotated_boxes[:, 0] = (boxes[:, 0] + boxes[:, 2]) / 2.0 | |
| rotated_boxes[:, 1] = (boxes[:, 1] + boxes[:, 3]) / 2.0 | |
| rotated_boxes[:, 2] = boxes[:, 2] - boxes[:, 0] | |
| rotated_boxes[:, 3] = boxes[:, 3] - boxes[:, 1] | |
| err_msg = "Rotated NMS incompatible between CPU and reference implementation for IoU={}" | |
| for iou in [0.2, 0.5, 0.8]: | |
| keep_ref = self.reference_horizontal_nms(boxes, scores, iou) | |
| keep = nms_rotated(rotated_boxes, scores, iou) | |
| self.assertLessEqual(nms_edit_distance(keep, keep_ref), 1, err_msg.format(iou)) | |
| def test_nms_rotated_0_degree_cuda(self): | |
| self.test_nms_rotated_0_degree_cpu(device="cuda") | |
| def test_nms_rotated_90_degrees_cpu(self): | |
| N = 1000 | |
| boxes, scores = self._create_tensors(N) | |
| rotated_boxes = torch.zeros(N, 5) | |
| rotated_boxes[:, 0] = (boxes[:, 0] + boxes[:, 2]) / 2.0 | |
| rotated_boxes[:, 1] = (boxes[:, 1] + boxes[:, 3]) / 2.0 | |
| # Note for rotated_boxes[:, 2] and rotated_boxes[:, 3]: | |
| # widths and heights are intentionally swapped here for 90 degrees case | |
| # so that the reference horizontal nms could be used | |
| rotated_boxes[:, 2] = boxes[:, 3] - boxes[:, 1] | |
| rotated_boxes[:, 3] = boxes[:, 2] - boxes[:, 0] | |
| rotated_boxes[:, 4] = torch.ones(N) * 90 | |
| err_msg = "Rotated NMS incompatible between CPU and reference implementation for IoU={}" | |
| for iou in [0.2, 0.5, 0.8]: | |
| keep_ref = self.reference_horizontal_nms(boxes, scores, iou) | |
| keep = nms_rotated(rotated_boxes, scores, iou) | |
| self.assertLessEqual(nms_edit_distance(keep, keep_ref), 1, err_msg.format(iou)) | |
| def test_nms_rotated_180_degrees_cpu(self): | |
| N = 1000 | |
| boxes, scores = self._create_tensors(N) | |
| rotated_boxes = torch.zeros(N, 5) | |
| rotated_boxes[:, 0] = (boxes[:, 0] + boxes[:, 2]) / 2.0 | |
| rotated_boxes[:, 1] = (boxes[:, 1] + boxes[:, 3]) / 2.0 | |
| rotated_boxes[:, 2] = boxes[:, 2] - boxes[:, 0] | |
| rotated_boxes[:, 3] = boxes[:, 3] - boxes[:, 1] | |
| rotated_boxes[:, 4] = torch.ones(N) * 180 | |
| err_msg = "Rotated NMS incompatible between CPU and reference implementation for IoU={}" | |
| for iou in [0.2, 0.5, 0.8]: | |
| keep_ref = self.reference_horizontal_nms(boxes, scores, iou) | |
| keep = nms_rotated(rotated_boxes, scores, iou) | |
| self.assertLessEqual(nms_edit_distance(keep, keep_ref), 1, err_msg.format(iou)) | |
| class TestScriptable(unittest.TestCase): | |
| def setUp(self): | |
| class TestingModule(torch.nn.Module): | |
| def forward(self, boxes, scores, threshold): | |
| return nms_rotated(boxes, scores, threshold) | |
| self.module = TestingModule() | |
| def test_scriptable_cpu(self): | |
| m = deepcopy(self.module).cpu() | |
| _ = torch.jit.script(m) | |
| def test_scriptable_cuda(self): | |
| m = deepcopy(self.module).cuda() | |
| _ = torch.jit.script(m) | |
| if __name__ == "__main__": | |
| unittest.main() | |