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from unittest import TestCase |
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import numpy as np |
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import torch |
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from mmdet3d.models.dense_heads import MonoFlexHead |
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class TestMonoFlexHead(TestCase): |
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def test_monoflex_head_loss(self): |
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"""Tests MonoFlex head loss and inference.""" |
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input_metas = [dict(img_shape=(110, 110), pad_shape=(128, 128))] |
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monoflex_head = MonoFlexHead( |
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num_classes=3, |
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in_channels=64, |
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use_edge_fusion=True, |
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edge_fusion_inds=[(1, 0)], |
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edge_heatmap_ratio=1 / 8, |
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stacked_convs=0, |
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feat_channels=64, |
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use_direction_classifier=False, |
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diff_rad_by_sin=False, |
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pred_attrs=False, |
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pred_velo=False, |
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dir_offset=0, |
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strides=None, |
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group_reg_dims=((4, ), (2, ), (20, ), (3, ), (3, ), (8, 8), (1, ), |
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(1, )), |
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cls_branch=(256, ), |
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reg_branch=((256, ), (256, ), (256, ), (256, ), (256, ), (256, ), |
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(256, ), (256, )), |
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num_attrs=0, |
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bbox_code_size=7, |
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dir_branch=(), |
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attr_branch=(), |
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bbox_coder=dict( |
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type='MonoFlexCoder', |
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depth_mode='exp', |
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base_depth=(26.494627, 16.05988), |
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depth_range=[0.1, 100], |
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combine_depth=True, |
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uncertainty_range=[-10, 10], |
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base_dims=((3.8840, 1.5261, 1.6286, 0.4259, 0.1367, 0.1022), |
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(0.8423, 1.7607, 0.6602, 0.2349, 0.1133, 0.1427), |
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(1.7635, 1.7372, 0.5968, 0.1766, 0.0948, 0.1242)), |
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dims_mode='linear', |
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multibin=True, |
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num_dir_bins=4, |
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bin_centers=[0, np.pi / 2, np.pi, -np.pi / 2], |
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bin_margin=np.pi / 6, |
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code_size=7), |
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conv_bias=True, |
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dcn_on_last_conv=False) |
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feats = [torch.rand([1, 64, 32, 32], dtype=torch.float32)] |
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cls_score, out_reg = monoflex_head.forward(feats, input_metas) |
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self.assertEqual(cls_score[0].shape, torch.Size([1, 3, 32, 32]), |
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'the shape of cls_score should be [1, 3, 32, 32]') |
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self.assertEqual(out_reg[0].shape, torch.Size([1, 50, 32, 32]), |
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'the shape of out_reg should be [1, 50, 32, 32]') |
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