| _base_ = ['./multiview-dfm_r101-dcn_16xb2_waymoD5-3d-3class.py'] | |
| model = dict( | |
| bbox_head=dict( | |
| _delete_=True, | |
| type='CenterHead', | |
| in_channels=256, | |
| tasks=[ | |
| dict(num_class=1, class_names=['Pedestrian']), | |
| dict(num_class=1, class_names=['Cyclist']), | |
| dict(num_class=1, class_names=['Car']), | |
| ], | |
| common_heads=dict(reg=(2, 2), height=(1, 2), dim=(3, 2), rot=(2, 2)), | |
| share_conv_channel=64, | |
| bbox_coder=dict( | |
| type='CenterPointBBoxCoder', | |
| post_center_range=[-35.0, -75.0, -2, 75.0, 75.0, 4], | |
| pc_range=[-35.0, -75.0, -2, 75.0, 75.0, 4], | |
| max_num=2000, | |
| score_threshold=0, | |
| out_size_factor=1, | |
| voxel_size=(.50, .50), | |
| code_size=7), | |
| separate_head=dict( | |
| type='SeparateHead', init_bias=-2.19, final_kernel=3), | |
| loss_cls=dict(type='mmdet.GaussianFocalLoss', reduction='mean'), | |
| loss_bbox=dict( | |
| type='mmdet.L1Loss', reduction='mean', loss_weight=0.25), | |
| norm_bbox=True), | |
| train_cfg=dict( | |
| _delete_=True, | |
| grid_size=[220, 300, 1], | |
| voxel_size=(0.5, 0.5, 6), | |
| out_size_factor=1, | |
| dense_reg=1, | |
| gaussian_overlap=0.1, | |
| max_objs=500, | |
| min_radius=2, | |
| code_weights=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], | |
| point_cloud_range=[-35.0, -75.0, -2, 75.0, 75.0, 4]), | |
| test_cfg=dict( | |
| _delete_=True, | |
| post_center_limit_range=[-35.0, -75.0, -2, 75.0, 75.0, 4], | |
| max_per_img=4096, | |
| max_pool_nms=False, | |
| min_radius=[0.5, 2, 6], | |
| score_threshold=0, | |
| out_size_factor=1, | |
| voxel_size=(0.5, 0.5), | |
| nms_type='circle', | |
| pre_max_size=2000, | |
| post_max_size=200, | |
| nms_thr=0.2)) | |