OMERO ROIs¶
OMERO Python library providing utilities for handling regions of interest.
- exception omero_rois.InvalidBinaryImage(msg='Invalid labels found')[source]¶
Exception thrown when invalid labels are found
- exception omero_rois.NoMaskFound(msg='No mask found')[source]¶
Exception thrown when no foreground pixels were found in a mask
- omero_rois.mask_from_binary_image(binim, rgba=None, z=None, c=None, t=None, text=None, raise_on_no_mask=True)[source]¶
Create a mask shape from a binary image (background=0)
- Parameters:
binim (numpy.array) – Binary 2D array, must contain values [0, 1] only
int-4-tuple (rgba) – Optional (red, green, blue, alpha) colour
z – Optional Z-index for the mask
c – Optional C-index for the mask
t – Optional T-index for the mask
text – Optional text for the mask
raise_on_no_mask – If True (default) throw an exception if no mask found, otherwise return an empty Mask
- Returns:
An OMERO mask
- Raises:
NoMaskFound – If no labels were found
InvalidBinaryImage – If the maximum labels is greater than 1
- omero_rois.masks_from_label_image(labelim, rgba=None, z=None, c=None, t=None, text=None, raise_on_no_mask=True)[source]¶
Create mask shapes from a label image (background=0)
- Parameters:
labelim (numpy.array) – 2D label array
int-4-tuple (rgba) – Optional (red, green, blue, alpha) colour
z – Optional Z-index for the mask
c – Optional C-index for the mask
t – Optional T-index for the mask
text – Optional text for the mask
raise_on_no_mask – If True (default) throw an exception if no mask found, otherwise return an empty Mask
- Returns:
A list of OMERO masks in label order ([] if no labels found)
- omero_rois.masks_to_labels(masks: List[omero.model.MaskI], mask_shape: Tuple[int, ...], ignored_dimensions: Set[str] = None, check_overlaps: bool = True) Tuple[numpy.ndarray, Dict[int, str], Dict[int, Dict]][source]¶
- Parameters:
List[MaskI] (masks) – List of OMERO masks
5-tuple (mask_shape) – the image dimensions (T, C, Z, Y, X), taking into account ignored_dimensions
Set[str] (ignored_dimensions) – Ignore these dimensions and set size to 1
bool (check_overlaps) – Whether to check for overlapping masks or not
- Returns:
Label image with size mask_shape as well as color metadata and dict of other properties.