deeplabv3_resnet50

torchvision.models.segmentation.deeplabv3_resnet50(pretrained: bool = False, progress: bool = True, num_classes: int = 21, aux_loss: Optional[bool] = None, pretrained_backbone: bool = True) → torchvision.models.segmentation.deeplabv3.DeepLabV3

Constructs a DeepLabV3 model with a ResNet-50 backbone.

Parameters

• pretrained (bool) – If True, returns a model pre-trained on COCO train2017 which contains the same classes as Pascal VOC

• progress (bool) – If True, displays a progress bar of the download to stderr

• num_classes (int) – number of output classes of the model (including the background)

• aux_loss (bool, optional) – If True, it uses an auxiliary loss

• pretrained_backbone (bool) – If True, the backbone will be pre-trained.

Examples using deeplabv3_resnet50:

Visualization utilities