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Commit 62565405 authored by liyinhao's avatar liyinhao
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change test_indoor_eval data

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tests/test_dataset/test_indoor_eval.py
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import numpy as np import numpy as np
import torch
from mmdet3d.core.evaluation.indoor_eval import indoor_eval from mmdet3d.core.evaluation.indoor_eval import indoor_eval
def test_indoor_eval(): def test_indoor_eval():
det_infos = [[[[ det_infos = [[[[
17.0, 4.0,
[ [
3.2112048e+00, 5.6918913e-01, -8.6143613e-04, 1.1942449e-01, 2.8734498, -0.187645, -0.02600911, 0.6761766, 0.56542563,
1.2988183e+00, 1.9952521e-01, 0.0000000e+00 0.5953976, 0.
], ], 0.9980684
torch.as_tensor(0.9965866)
], ],
[ [
17.0, 4.0,
[ [
3.248133, 0.4324184, 0.20038621, 0.17225507, 0.4031701, -3.2346897, 0.07118589, 0.73209894,
1.2736976, 0.32598814, 0. 0.8711227, 0.5148243, 0.
], ], 0.9747082
torch.as_tensor(0.99507546)
], ],
[ [
3.0, 3.0,
[ [
-1.2793612, -2.3155289, 0.15598366, 1.2822601, -1.274147, -2.351935, 0.07428858, 1.4534658,
2.2253945, 0.8361754, 0. 2.563081, 0.8587492, 0.
], ], 0.9709939
torch.as_tensor(0.9916463)
],
[
4.0,
[
2.8716104, -0.26416883, -0.04933786, 0.8190681,
0.60294986, 0.5769499, 0.
],
torch.as_tensor(0.9702634)
], ],
[ [
17.0, 17.0,
[ [
-2.2109854, 0.19445783, -0.01614259, 0.40659013, 3.2214177, 0.7899204, 0.03836718, 0.05321002,
0.35370222, 0.3290567, 0. 1.2607929, 0.1411697, 0.
], ], 0.9482147
torch.as_tensor(0.95803124)
], ],
[ [
4.0, 2.0,
[ [
0.18409574, -3.3322976, 0.13188198, 0.960528, -1.6804854, 2.399011, -0.13099639, 0.5608963,
0.91082716, 0.59325826, 0. 0.5052759, 0.6770297, 0.
], ], 0.84311247
torch.as_tensor(0.9483817) ]]],
], [[[
17.0,
[
3.2112048e+00, 5.6918913e-01, -8.6143613e-04,
1.1942449e-01, 1.2988183e+00, 1.9952521e-01,
0.0000000e+00
], 0.9965866
],
[ [
17.0, 17.0,
[ [
1.9499326, 2.0099056, 0.32836294, 0.98528206, 3.248133, 0.4324184, 0.20038621, 0.17225507,
1.0611539, 1.2197046, 0. 1.2736976, 0.32598814, 0.
], ], 0.99507546
torch.as_tensor(0.92196786)
], ],
[ [
2.0, 3.0,
[ [
-1.6204697, 2.3374724, 0.06042781, 0.49681002, -1.2793612, -2.3155289, 0.15598366, 1.2822601,
0.44362187, 0.47277915, 0. 2.2253945, 0.8361754, 0.
], ], 0.9916463
torch.as_tensor(0.87960094)
], ],
[ [
17.0, 4.0,
[ [
2.1414487, -1.7601899, 0.17694443, 1.0071366, 2.8716104, -0.26416883, -0.04933786, 0.8190681,
2.211764, 1.4690719, 0. 0.60294986, 0.5769499, 0.
], ], 0.9702634
torch.as_tensor(0.8586809)
], ],
[ [
17.0, 17.0,
[ [
-0.0484907, -3.639972, 0.41367513, 3.948648, -2.2109854, 0.19445783, -0.01614259, 0.40659013,
1.3692774, 1.0810001, 0. 0.35370222, 0.3290567, 0.
], ], 0.95803124
torch.as_tensor(0.80680436)
]]]] ]]]]
label2cat = { label2cat = {
...@@ -109,10 +99,59 @@ def test_indoor_eval(): ...@@ -109,10 +99,59 @@ def test_indoor_eval():
gt_annos = [{ gt_annos = [{
'gt_num': 'gt_num':
12, 12,
'name': [ 'gt_boxes_upright_depth':
'table', 'curtain', 'sofa', 'bookshelf', 'picture', 'chair', np.array([[
'chair', 'garbagebin', 'table', 'chair', 'chair', 'garbagebin' 2.54621506, -0.89397144, 0.54144311, 2.90430856, 1.78370309,
0.93826824
], ],
[
3.36553669, 0.31014189, 0.38758934, 1.2504847,
0.71281439, 0.3908577
],
[
0.17272574, 2.90289116, 0.27966365, 0.56292468,
0.8512187, 0.4987641
],
[
2.39521956, 1.67557895, 0.40407273, 1.23511314,
0.49469376, 0.62720448
],
[
-2.41815996, -1.69104958, 0.22304082, 0.55816364,
0.48154473, 0.66580439
],
[
-0.18044823, 2.9227581, 0.24480903, 0.36165208,
0.44468427, 0.53103662
],
[
-2.44398379, -2.1610918, 0.23631772, 0.52229881,
0.63388562, 0.66596919
],
[
-2.01452827, -2.9558928, 0.8139953, 1.61732554,
0.60224247, 1.79295814
],
[
-0.61519569, 3.24365234, 1.24335742, 2.11988783,
0.26006722, 1.77748263
],
[
-2.64330673, 0.59929442, 1.59422684, 0.07352924,
0.28620502, 0.35408139
],
[
-0.58128822, 3.23699641, 0.06050609, 1.94151425,
0.16413498, 0.20168215
],
[
0.15343043, 2.24693251, 0.22470728, 0.49632657,
0.47379827, 0.43063563
]]),
'class': [3, 4, 4, 17, 2, 2, 2, 7, 11, 8, 17, 2]
}, {
'gt_num':
12,
'gt_boxes_upright_depth': 'gt_boxes_upright_depth':
np.array([[ np.array([[
3.48649406, 0.24238291, 0.48358256, 1.34014034, 0.72744983, 3.48649406, 0.24238291, 0.48358256, 1.34014034, 0.72744983,
...@@ -176,21 +215,29 @@ def test_indoor_eval(): ...@@ -176,21 +215,29 @@ def test_indoor_eval():
table_rec_25 = ret_value['table_rec_0.25'] table_rec_25 = ret_value['table_rec_0.25']
chair_rec_25 = ret_value['chair_rec_0.25'] chair_rec_25 = ret_value['chair_rec_0.25']
mAR_25 = ret_value['mAR_0.25'] mAR_25 = ret_value['mAR_0.25']
sofa_AP_50 = ret_value['sofa_AP_0.50']
table_AP_50 = ret_value['table_AP_0.50'] table_AP_50 = ret_value['table_AP_0.50']
chair_AP_50 = ret_value['chair_AP_0.50']
mAP_50 = ret_value['mAP_0.50'] mAP_50 = ret_value['mAP_0.50']
sofa_rec_50 = ret_value['sofa_rec_0.50']
table_rec_50 = ret_value['table_rec_0.50'] table_rec_50 = ret_value['table_rec_0.50']
chair_rec_50 = ret_value['chair_rec_0.50']
mAR_50 = ret_value['mAR_0.50'] mAR_50 = ret_value['mAR_0.50']
assert garbagebin_AP_25 == 0.5 assert garbagebin_AP_25 == 0.25
assert sofa_AP_25 == 1.0 assert sofa_AP_25 == 1.0
assert table_AP_25 == 1.0 assert table_AP_25 == 0.75
assert chair_AP_25 == 0.25 assert chair_AP_25 == 0.125
assert abs(mAP_25 - 0.392857) < 0.001 assert abs(mAP_25 - 0.303571) < 0.001
assert garbagebin_rec_25 == 0.5 assert garbagebin_rec_25 == 0.25
assert sofa_rec_25 == 1.0 assert sofa_rec_25 == 1.0
assert table_rec_25 == 1.0 assert table_rec_25 == 0.75
assert chair_rec_25 == 0.25 assert chair_rec_25 == 0.125
assert abs(mAR_25 - 0.392857) < 0.001 assert abs(mAR_25 - 0.303571) < 0.001
assert table_AP_50 == 0.5 assert sofa_AP_50 == 0.25
assert abs(mAP_50 - 0.0714) < 0.001 assert abs(table_AP_50 - 0.416667) < 0.001
assert chair_AP_50 == 0.125
assert abs(mAP_50 - 0.113095) < 0.001
assert sofa_rec_50 == 0.5
assert table_rec_50 == 0.5 assert table_rec_50 == 0.5
assert abs(mAR_50 - 0.0714) < 0.001 assert chair_rec_50 == 0.125
assert abs(mAR_50 - 0.160714) < 0.001
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