logger.info('Distributed training: {}'.format(distributed))# set random seedsifargs.seedisnotNone: logger.info('Set random seed to {}'.format(args.seed)) set_random_seed(args.seed)# ipdb.set_trace(context=35)# 搭建模型model = build_detector( cfg.model, train_cfg=cfg.train_cfg, test_...
下面是一个简单的代码示例,演示如何使用CustomEpochBasedRunner进行训练: frommmdet3d.apisimportset_random_seedfrommmcvimportConfigfrommmdet3d.datasetsimportbuild_datasetfrommmdet3d.modelsimportbuild_modelfrommmdet3d.apisimporttrain_modelfrommmdet3d.modelsimportCustomEpochBasedRunner# 设置随机种子set_random_seed(0)...
File "tools/train.py", line 16, in from mmdet.apis import set_random_seed, train_detector File "/home/zzf/Desktop/D2Det/tools/../mmdet/apis/init.py", line 1, in from .inference import (async_inference_detector, inference_detector, File "/home/zzf/Desktop/D2Det/tools/../mmdet/apis/...
MMDistributedDataParallelfrommmcv.runnerimport(HOOKS,DistSamplerSeedHook,EpochBasedRunner,Fp16OptimizerHook,OptimizerHook,build_optimizer,build_runner)frommmcv.utilsimportbuild_from_cfgfrommmdet.coreimportDistEvalHook,EvalHookfrommmdet.datasetsimport(build_dataloader,build...
np.random.seed(seed) random.seed(seed) torch.cuda.manual_seed_all(seed) # torch.autograd.set_detect_anomaly(True) 检测梯度计算失败位置 class ArgParse: def __init__(self) -> None: self.batch_size = 16 self.lr = 0.001 self.epochs = 10 ...
No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' sys.platform: linux Python: 3.8.13 (default, Mar 28 2022, 11:38:47) [GCC 7.5.0] CUDA available: False numpy_random_seed: 2147483648 GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0 PyTorch: 1.12.1 PyTorch compiling det...
('--seed',type=int,default=None,help='random seed')parser.add_argument('--deterministic',action='store_true',help='whether to set deterministic options for CUDNN backend.')parser.add_argument('--options',nargs='+',action=DictAction,help='override some settings in the used config, the ...
When I run 'python tools\train.py configs\yolox\yolox_x_8xb8-300e_coco.py', it reported the following error,My detection class is one, which I have set in 'mmdet\datasets\coco.py': METAINFO = { 'classes':('pig',), 'palette':[(220,60,20)] } ...
usually for indoor dataset. - 'Camera': Box in camera coordinates. filter_empty_gt (bool): Whether to filter the data with empty GT. If it's set to be True, the example with empty annotations after data pipeline will be dropped and a random example will be chosen in `__getitem__`....
hi, it's odd that this error occured when training DOTA for I check the code and seems no problem : Traceback (most recent call last): File "tools/train.py", line 9, in <module> from mmdet.apis import (get_root_logger, init_dist, set_ran...