针对您提出的问题 cannot import name 'build_model' from 'mmdet3d.models',这里有几个可能的解决步骤和建议,您可以根据这些建议逐一排查问题: 1. 检查mmdet3d.models模块 首先,您需要确认mmdet3d.models模块中是否确实存在build_model函数或类。这通常可以通过查看该模块的文档或源代码来完成。如果build_model不存在...
CenterPoint model 生成epoch文件 介绍 最大的感受就是 MMDetection 3D 太强大了。一个强大的框架,融合了多种模型和训练方法,使用起来也很方便。 MMEngine 是一个基于 PyTorch 实现的,用于训练深度学习模型的基础库,支持在 Linux、Windows、macOS 上运行。它具有如下三个特性: 通用且强大的执行器: 支持用少量代...
定义的模型继承自Base3DDetector,Base3DDetector继承自BaseDetector,BaseDetector继承自BaseModel,BaseModel中有train_step,val_step,而_train_loop是build_train_loop(train_cfg)的返回值 train_step定义如下: def train_step(self, data: Union[dict, tuple, list], optim_wrapper: OptimWrapper) -> Dict[str, ...
model-index.yml requirements.txt setup.cfg setup.py Breadcrumbs mmdetection3d /mmdet3d /datasets / nuscenes_mono_dataset.py Latest commit ZCMax [Enhance] Update Registry in MMDet3D (#1412) Apr 27, 2022 0287048·Apr 27, 2022 History History...
build the model from a config file and a checkpoint file model = init_model(config_file, checkpoint_file, device='cuda:0') # test a single bin pcd = os.path.join(base_dir, r'demo/data/kitti/kitti_000008.bin') result, data = inference_detector(model, pcd) # show the results show...
model = dict( type='VoxelNet', data_preprocessor=dict( type='Det3DDataPreprocessor', voxel=True, voxel_layer=dict( max_num_points=32, point_cloud_range=[0, -39.68, -3, 69.12, 39.68, 1], voxel_size=[0.16, 0.16, 4], max_voxels=(16000, 40000))), ...
build the model from a config file and a checkpoint file model = init_model(config_file, checkpoint_file, device='cuda:0') # test a single bin pcd = os.path.join(base_dir, r'demo/data/kitti/kitti_000008.bin') result, data = inference_detector(model, pcd) # show the results show...
('configs/pointpillars/pointpillars_kitti.py')# 构建数据集和模型dataset=build_dataset(cfg.data.train)model=build_model(cfg.model)# 创建训练器runner=CustomEpochBasedRunner(model=model,batch_processor=None,optimizer=None,work_dir='./work_dir',logger=None,meta=None)# 开始训练runner.run(data_loaders...
error:KeyError: <Task.VOXEL_DETECTION: 'VoxelDetection'> Or is there any other approaches to deploying BEVFormer? I read the codes of BEVFormer and there are some modules related todeformable attentionimplemented based onmmcv. So I think it is not easy to build an TRT engine directly....
'setuptools.command.build_ext', 'torch.utils.cpp_extension', 'mmcv.utils.parrots_wrapper', 'mmcv.utils.env', 'torch.utils.model_zoo', 'mmcv.utils.hub', 'mmcv.utils.logging', 'mmcv.utils.parrots_jit', 'mmcv.utils.registry', 'mmcv.utils.seed', 'mmcv.utils.trace', 'mmcv.utils', '...