distributed参数一般是影响这几个地方:init_dist(这里别忘了);dataloader;model;eval_hook DDP train find_unused_parameters用来控制model.forward输出参与gradient运算。因为MMCV中segmentor(encoder_decoder)就是nn.Module,另外输出一般是个dict,所以如果没有改变(比如后面提到的情况),正常情况下设置: model = MMDistribu...
from mmdet.apis import init_detector, inference_detector, show_result_pyplotconfig_file = 'configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'# 从 model zoo 下载 checkpoint 并放在 `checkpoints/` 文件下# 网址为: http://download.openmmlab.com/mmdetection...
AI代码解释 # https://github.com/open-mmlab/mmcv/blob/master/mmcv/runner/hooks/checkpoint.pyclassCheckpointHook(Hook):"""保存 checkpoint"""def__init__(self,interval=-1,by_epoch=True,save_optimizer=True,out_dir=None,max_keep_ckpts=-1,save_last=True,sync_buffer=False,file_client_args=None...
class BaseRunner(metaclass=ABCMeta): def __init__(self,batch_processor): # batch_processor: 这是一个计算loss的函数,输入已经固定(model, data, train_mode),输出的loss是固定的在optimizer.py函数中after_train_iter进行反向传播,如果有多个loss,可以修改batch_processor函数,或者修改after_train_iter中的反...
./mmcv.runner.base_runner.py class BaseRunner(metaclass=ABCMeta): def __init__(self,batch_processor): # batch_processor: 这是一个计算loss的函数,输入已经固定(model, data, train_mode),输出的loss是固定的在optimizer.py函数中after_train_iter进行反向传播,如果有多个loss,可以修改batch_processor函数...
from mmseg.apis import init_segmentor, inference_segmentor from mmseg.core.evaluation import get_palette import mmcv # 指定模型配置文件和权重文件路径 config_file = 'configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k.py' checkpoint_file = 'upernet_swin_tiny_patch4_window7_512x512...
这里顺带回顾一下import的知识点,检测时调用的init_detector,inference_detector,show_result_pyplot都是在mmdetection-master/mmdet/apis/inference.py文件中的函数对象,而从相对路径mmdet.apis导入模块时,由于目录中包含__init__.py,实际会执行该目录下__init__.py内的代码,如下所示 ...
执行conda activate 环境名,报错在 在终端进入*\Anaconda\condabin路径,执行conda init*,执行完后重启终端。 再用conda activate 环境名进入虚拟环境... 重装conda 重装Conda是因为想重装tensorflow,结果竟然报了各种各样稀奇古怪的错误:我贴一下自己见过的报错 The environment is inconsistent, please check the packa...
# https://github.com/open-mmlab/mmcv/blob/master/mmcv/runner/hooks/checkpoint.pyclass CheckpointHook(Hook):"""保存 checkpoint"""def __init__(self,interval=-1,by_epoch=True,save_optimizer=True,out_dir=None,max_keep_ckpts=-1,save_last=True,sync_buffer=False,file_client_args=None,**kwarg...
from mmdet3d.apis import init_random_seed, train_model File "/usr/local/lib/python3.8/dist-packages/mmdet3d/apis/__init__.py", line 2, in <module> from .inference import (convert_SyncBN, inference_detector, File "/usr/local/lib/python3.8/dist-packages/mmdet3d/apis/inference.py", line...