116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) # 裁剪大小 crop_size = (512, 512) train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', reduce_zero_label=False), dict(type='Resize', img_scale=(720,...
__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=...
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...
/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, ' ...
label (torch.Tensor): The learning label of the prediction. Note: In bce loss, label < 0 is invalid. weight (torch.Tensor, optional): Sample-wise loss weight. reduction (str, optional): The method used to reduce the loss. Options are "none", "mean" and "sum". avg_factor (int, ...
for logit, label in zip(logits, labels) ] loss = weight_reduce_loss( torch.stack(loss), None, reduction, avg_factor) else: loss = lovasz_hinge_flat( *flatten_binary_logits(logits, labels, ignore_index)) return loss def lovasz_softmax_flat(probs, labels, classes='present',...
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/__init__.py中添加声明 ...
label_map (dict): Mapping old labels to new labels. Default: dict(). reduce_zero_label (bool): Whether ignore zero label. Default: False. Returns: ndarray: The intersection of prediction and ground truth histogram on all classes. ndarray: The union of prediction and ground truth histogram ...
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