File size: 3,172 Bytes
34d1f8b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import shutil
import time
from unittest import TestCase
from unittest.mock import Mock
import numpy as np
import torch
from mmengine.structures import InstanceData
from mmdet3d.engine.hooks import Det3DVisualizationHook
from mmdet3d.structures import Det3DDataSample, LiDARInstance3DBoxes
from mmdet3d.visualization import Det3DLocalVisualizer
class TestVisualizationHook(TestCase):
def setUp(self) -> None:
Det3DLocalVisualizer.get_instance('visualizer')
pred_instances_3d = InstanceData()
pred_instances_3d.bboxes_3d = LiDARInstance3DBoxes(
torch.tensor(
[[8.7314, -1.8559, -1.5997, 1.2000, 0.4800, 1.8900, -1.5808]]))
pred_instances_3d.labels_3d = torch.tensor([0])
pred_instances_3d.scores_3d = torch.tensor([0.8])
pred_det3d_data_sample = Det3DDataSample()
pred_det3d_data_sample.set_metainfo({
'num_pts_feats':
4,
'lidar2img':
np.array([[
6.02943734e+02, -7.07913286e+02, -1.22748427e+01,
-1.70942724e+02
],
[
1.76777261e+02, 8.80879902e+00, -7.07936120e+02,
-1.02568636e+02
],
[
9.99984860e-01, -1.52826717e-03, -5.29071223e-03,
-3.27567990e-01
],
[
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
1.00000000e+00
]]),
'img_path':
osp.join(
osp.dirname(__file__),
'../../data/kitti/training/image_2/000000.png'),
'lidar_path':
osp.join(
osp.dirname(__file__),
'../../data/kitti/training/velodyne_reduced/000000.bin')
})
pred_det3d_data_sample.pred_instances_3d = pred_instances_3d
self.outputs = [pred_det3d_data_sample] * 2
def test_after_val_iter(self):
runner = Mock()
runner.iter = 1
hook = Det3DVisualizationHook()
hook.after_val_iter(runner, 1, {}, self.outputs)
def test_after_test_iter(self):
runner = Mock()
runner.iter = 1
hook = Det3DVisualizationHook(draw=True)
hook.after_test_iter(runner, 1, {}, self.outputs)
self.assertEqual(hook._test_index, 2)
# test
timestamp = time.strftime('%Y%m%d_%H%M%S', time.localtime())
test_out_dir = timestamp + '1'
runner.work_dir = timestamp
runner.timestamp = '1'
hook = Det3DVisualizationHook(draw=False, test_out_dir=test_out_dir)
hook.after_test_iter(runner, 1, {}, self.outputs)
self.assertTrue(not osp.exists(f'{timestamp}/1/{test_out_dir}'))
hook = Det3DVisualizationHook(draw=True, test_out_dir=test_out_dir)
hook.after_test_iter(runner, 1, {}, self.outputs)
self.assertTrue(osp.exists(f'{timestamp}/1/{test_out_dir}'))
shutil.rmtree(f'{timestamp}')
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