lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False) # runtime settings runner = dict(type='IterBasedRunner', max_iters=20000) # 保存 checkpoints checkpoint_config = dict(by_epoch=False, interval=500) evaluation = dict(interval=500, metric='mIoU', pre_eval=True...
# configs/ours/fixmatch_ous.pycustom_imports=dict(imports=['mmcv_custom.runner'],allow_failed_imports=False)runner=dict(type='CustomRunner',max_iters=400)# 160000checkpoint_config=dict(by_epoch=False,interval=400,max_keep_ckpts=1)# 1000evaluation=dict(interval=1,metric='mIoU',save_best='mIo...
frommmseg.apisimportinit_segmentor, inference_segmentor, show_result_pyplotfrommmseg.core.evaluationimportget_palette config_file ='./configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py'checkpoint_file ='./checkpoints/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth'# build ...
checkpoint_config = dict(by_epoch=False, interval=16000) evaluation = dict(interval=16000, metric='mIoU') work_dir = '' gpu_ids = [0,1]475 changes: 475 additions & 0 deletions 475 segmentation task/mmseg/models/backbones/vit.py Original file line numberDiff line numberDiff line change...
用于存放预训练模型权重文件os.mkdir('checkpoint')# 创建 outputs 文件夹,用于存放预测结果os.mkdir('outputs')# 创建 data 文件夹,用于存放图片和视频素材os.mkdir('data')# 创建 图表 文件夹,用于存放生成的图表os.mkdir('图表')# 创建 Zihao-Configs 文件夹,用于存放自己的语义分割模型的 config 配置文件os...
num_classes=150ignore_index=255config_file='pspnet_r50-d8_512x1024_40k_cityscapes.py'checkpoint_file='pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth'mainFolder="/images/validation/"labelFolder="/annotations/validation/"outFolders="/result/label/"myFolders=os.listdir(mainFolder...
frommmseg.apisimportinit_model, inference_model, show_result_pyplot# Init the model from the config and the checkpointcheckpoint_path = './work_dirs/tutorial/iter_200.pth' model = init_model(cfg, checkpoint_path, 'cuda:0') img = mmcv.imread('iccv09Data/images/6000124.jpg')result= infe...
cfg = mmcv.Config.fromfile('config.py') model = builder.build_model(cfg.model) load_checkpoint(model, 'checkpoint.pth') 在上述示例中,我们首先自定义了一个名为MySegModel的分割模型,然后通过装饰器@MODELS.register_module()将其注册为MySegModelWrapper。最后,我们可以使用builder.build_model()函数根据...
checkpoint = CheckpointLoader.load_checkpoint( self.init_cfg['checkpoint'], logger=None, map_location='cpu') rec_state_dict = checkpoint.copy() para_prefix = 'decode_head.rec_with_attnbias' prefix_len = len(para_prefix) + 1 for k, v in checkpoint.items(): rec_state_dict.pop...
checkpoint=dict( by_epoch=False, interval=2500, max_keep_ckpt=1, save_best='mIoU', type='CheckpointHook'), logger=dict(interval=100, log_metric_by_epoch=False, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'),