seg_map_suffix='.png', # 默认标注的后缀为‘.png’,根据数据修改 reduce_zero_label=False, # 管理0值标签,例:标签值为[0,1,2],当False时,num_classes=3,当True,num_classes=2 **kwargs) assert osp.exists(self.img_dir) # assert self.file_client.exists(self.img_dir) 在./mmseg/datasets/...
reduce_zero_label=False),dict(type='Resize',img_scale=scale,ratio_range=(0.5,2.0)),dict(type='RandomCrop',crop_size=crop_size,cat_max_ratio=0.75),dict(type='RandomFlip',prob=0.5),# dict(type='PhotoMetricDistortion'),dict(type='StrongAugCustom'),dict(type='Normalize',**img_norm_cfg)...
seg_map_suffix='.png', reduce_zero_label=False, **kwargs) -> None: super().__init__( img_suffix=img_suffix, seg_map_suffix=seg_map_suffix, reduce_zero_label=reduce_zero_label, **kwargs) assert fileio.exists( self.data_prefix['img_path'], backend_args=self.backend_args) mmsegme...
Describe the bug /home/lyk/lyk/mmsegmentation-1.0.0rc6/mmseg/datasets/transforms/loading.py:78: UserWarning:reduce_zero_labelwill be deprecated, if you would like to ignore the zero label, please setreduce_zero_label=Truewhen dataset initialized warnings.warn('reduce_zero_labelwill be deprecated,...
from.utilsimportget_class_weight,weight_reduce_loss defcross_entropy(pred, label, weight=None, class_weight=None, reduction='mean', avg_factor=None, ignore_index=-100, avg_non_ignore=False): """cross_entropy. The wrapper function for :func:`F.cross_entropy` ...
eps (float): Avoid dividing by zero. Default: 1e-3. reduction (str, optional): The method used to reduce the loss into a scalar. Defaults to 'mean'. Options are "none", "mean" and "sum". naive_dice (bool, optional): If false, use the dice ...
reduce_zero_label 参数 其他问题 openmmlab教程3-MMSeg 使用 3. MMSeg 使用 需要基础,首先得跑过一个完整的语义分割的网络模型,这样子学起来比较轻松 准备数据集 dataset 数据增强 准备网络模型model 准备训练train 设置优化器sgd,adawm 设置学习策略poly,step,cosine 设置损失函数CrossEntropy 设置评价指标miou 3.1...
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__init__( img_suffix='.png', seg_map_suffix='.png', reduce_zero_label=True, **kwargs) 3) 配置文件 创建config_camvid.py dataset_type = 'Camvid12' # 数据集的地址 data_root = r'E:\note\cv\data\CamVid_12' img_norm_cfg = dict( mean=[123.675, 116.28, 103.53], std=...
from.utilsimportget_class_weight,weight_reduce_loss defcross_entropy(pred, label, weight=None, class_weight=None, reduction='mean', avg_factor=None, ignore_index=-100, avg_non_ignore=False): """cross_entropy. The wrapper function for :func:`F.cross_entropy` ...