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Fix mask dimension in MaskRCNN docstring #1198

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Aug 5, 2019
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Fix mask dimension in MaskRCNN docstring #1198

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4 changes: 2 additions & 2 deletions torchvision/models/detection/mask_rcnn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ class MaskRCNN(FasterRCNN):
- boxes (FloatTensor[N, 4]): the ground-truth boxes in [x1, y1, x2, y2] format, with values
between 0 and H and 0 and W
- labels (Int64Tensor[N]): the class label for each ground-truth box
- masks (UInt8Tensor[N, 1, H, W]): the segmentation binary masks for each instance
- masks (UInt8Tensor[N, H, W]): the segmentation binary masks for each instance

The model returns a Dict[Tensor] during training, containing the classification and regression
losses for both the RPN and the R-CNN, and the mask loss.
Expand Down Expand Up @@ -278,7 +278,7 @@ def maskrcnn_resnet50_fpn(pretrained=False, progress=True,
- boxes (``FloatTensor[N, 4]``): the ground-truth boxes in ``[x1, y1, x2, y2]`` format, with values
between ``0`` and ``H`` and ``0`` and ``W``
- labels (``Int64Tensor[N]``): the class label for each ground-truth box
- masks (``UInt8Tensor[N, 1, H, W]``): the segmentation binary masks for each instance
- masks (``UInt8Tensor[N, H, W]``): the segmentation binary masks for each instance

The model returns a ``Dict[Tensor]`` during training, containing the classification and regression
losses for both the RPN and the R-CNN, and the mask loss.
Expand Down