环境：py3.8 + pytorch 1.8.1 + cuda 11.1

服务器Ubuntu版本：Ubuntu 22.04.1 LTS

环境配置过程：

conda create -n mmdet_py38 python=3.8    # 创建环境
conda activate mmdet_py38    # 激活环境
pip install torch==1.8.1+cu111 torchvision==0.9.1+cu111 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html    # 安装pytorch
# 使用 MIM 安装 MMEngine 和 MMCV
pip install -U openmim
mim install mmengine
mim install "mmcv==2.0.0"
pip install -v -e . #进入到项目文件夹下执行此命令

config文件：

_base_ = '../dino/dino-4scale_r50_8xb2-24e_coco.py'
model = dict(bbox_head=dict(num_classes=5))dataset_type = 'CocoDataset'
data_root = '/data/zy/dataset/project/Cooper001_withlabel/coco/'
classes = ('Inlet', 'Slightshort', 'Generalshort', 'Severeshort', 'Outlet')# Modify dataset related settings
metainfo = {'classes': ('Inlet', 'Slightshort', 'Generalshort', 'Severeshort', 'Outlet' ),}
#backend_args = Nonetrain_dataloader = dict(batch_size=2,num_workers=2,dataset=dict(data_root=data_root,metainfo=dict(classes=classes),ann_file='annotations/instances_train2017.json',data_prefix=dict(img='train2017/'),))
val_dataloader = dict(dataset=dict(data_root=data_root,metainfo=dict(classes=classes),ann_file='annotations/instances_val2017.json',data_prefix=dict(img='val2017/'),))val_evaluator = dict(ann_file=data_root + 'annotations/instances_val2017.json')# inference on test dataset and
# format the output results for submission.
test_dataloader = dict(batch_size=1,num_workers=2,persistent_workers=True,drop_last=False,sampler=dict(type='DefaultSampler', shuffle=False),dataset=dict(type=dataset_type,data_root=data_root,ann_file=data_root + 'annotations/instances_test2017.json',data_prefix=dict(img='test2017/'),test_mode=True,))
test_evaluator = dict(type='CocoMetric',metric='bbox',format_only=True,ann_file=data_root + 'annotations/instances_test2017.json',outfile_prefix='./work_dirs/coco_detection/test')#test_dataloader = val_dataloader
#test_evaluator = val_evaluatorevaluation = dict(interval=1, metric='bbox', classwise=True)  
load_from = '/data/zy/code/mmdetection-3.x/checkpoints/dino-4scale_r50_8xb2-12e_coco_20221202_182705-55b2bba2.pth'

训练指令：

CUDA_VISIBLE_DEVICES=1 python tools/train.py ./configs/demo/dino-4scale_r50_8xb2-24e_coco.py --work-dir ./work_dir/dino