torchvision.utils.draw_segmentation_masks(image: torch.Tensor, masks: torch.Tensor, alpha: float = 0.8, colors: Optional[Union[List[Union[str, Tuple[int, int, int]]], str, Tuple[int, int, int]]] = None)torch.Tensor[source]

Draws segmentation masks on given RGB image. The values of the input image should be uint8 between 0 and 255.

  • image (Tensor) – Tensor of shape (3, H, W) and dtype uint8.

  • masks (Tensor) – Tensor of shape (num_masks, H, W) or (H, W) and dtype bool.

  • alpha (float) – Float number between 0 and 1 denoting the transparency of the masks. 0 means full transparency, 1 means no transparency.

  • colors (color or list of colors, optional) – List containing the colors of the masks or single color for all masks. The color can be represented as PIL strings e.g. “red” or “#FF00FF”, or as RGB tuples e.g. (240, 10, 157). By default, random colors are generated for each mask.


Image Tensor, with segmentation masks drawn on top.

Return type

img (Tensor[C, H, W])

Examples using draw_segmentation_masks:

Repurposing masks into bounding boxes

Repurposing masks into bounding boxes

Repurposing masks into bounding boxes
Visualization utilities

Visualization utilities

Visualization utilities


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