input is a tensor of integral feature map, and the output is the segmentation logit. Returns: Tensor | tuple[Tensor]: Output tensor or tuple of tensors. """ if self.training: x_p, x_i, x_d = inputs x_p = self.p_head(x_p, self.p_cls_seg) x_i = self.i_head(...
img_suffix='.jpg', 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...
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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,...
point_label = point_sample( gt_semantic_seg.float(), points, mode='nearest', align_corners=self.align_corners) point_label = point_label.squeeze(1).long() loss = dict() if not isinstance(self.loss_decode, nn.ModuleList): losses_decode = [self.loss_decode] else: losses...
ignore_index (int | None): The label index to be ignored. Default: 255. loss_name (str): Name of the loss item. If you want this loss item to be included into the backward graph, `loss_` must be the prefix of the name. Defaults to 'loss_boundary'. """ def __init__(...
ignore_index (int | None): The label index to be ignored. Default: 255. loss_name (str): Name of the loss item. If you want this loss item to be included into the backward graph, `loss_` must be the prefix of the name. Defaults to 'loss_boundary'. """ def __init__(se...
python tools/test.py config文件路径 权重文件路径--eval mAp 可以看到mmseg训练是仅需要一个模型的配置文件,这里应该是把数据配置写到这个模型配置文件里的,我们去看一看这个文件包含什么 可以看到该文件包含模型文件_base_/models/deeplabv3plus_r50-d8.py,也包含数据配置文件pascal_voc12.py,还包括一些训练参数以及...
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) ...
__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=...