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import unittest
import torch
from mmengine import DefaultScope
from mmdet3d.registry import MODELS
from mmdet3d.testing import (create_detector_inputs, get_detector_cfg,
setup_seed)
class Test3DSSD(unittest.TestCase):
def test_3dssd(self):
import mmdet3d.models
assert hasattr(mmdet3d.models, 'SSD3DNet')
DefaultScope.get_instance('test_ssd3d', scope_name='mmdet3d')
setup_seed(0)
voxel_net_cfg = get_detector_cfg('3dssd/3dssd_4xb4_kitti-3d-car.py')
model = MODELS.build(voxel_net_cfg)
num_gt_instance = 3
packed_inputs = create_detector_inputs(
num_gt_instance=num_gt_instance, num_classes=1)
if torch.cuda.is_available():
model = model.cuda()
# test simple_test
with torch.no_grad():
data = model.data_preprocessor(packed_inputs, True)
torch.cuda.empty_cache()
results = model.forward(**data, mode='predict')
self.assertEqual(len(results), 1)
self.assertIn('bboxes_3d', results[0].pred_instances_3d)
self.assertIn('scores_3d', results[0].pred_instances_3d)
self.assertIn('labels_3d', results[0].pred_instances_3d)
losses = model.forward(**data, mode='loss')
self.assertGreater(losses['centerness_loss'], 0)
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