ExtractBatchMask
- class lib.infer.objects.ExtractBatchMask(centering: CenteringType, matrices: npt.NDArray[np.float32], storage_size: int = 0, masks: npt.NDArray[np.uint8] = <factory>)
Bases:
objectDataclass for holding information about masks produced by the extraction pipeline
- Parameters:
centering (CenteringType) – The centering type of the masks
matrices (npt.NDArray[np.float32]) – The normalized matrices required to take the masks from (0, 1) to full frame
storage_size (int) – The pixel size to store the mask at in the alignments file. Default: 0 (must be populated later)
masks (npt.NDArray[np.uint8]) – The masks for this batch. Default: empty array (must be populated later)
Attributes Summary
The pixel size to store the mask at in the alignments file
Methods Summary
append(mask_batch)Append the given mask batch object to this batch mask object
apply_mask(mask)Apply a boolean mask to the batch object.
Attributes Documentation
- storage_size: int = 0
The pixel size to store the mask at in the alignments file
Methods Documentation
- append(mask_batch: ExtractBatchMask) None
Append the given mask batch object to this batch mask object
- Parameters:
mask_batch (ExtractBatchMask) – The object containing data to be appended to this object
- Return type:
None
- apply_mask(mask: ndarray[tuple[Any, ...], dtype[bool]]) None
Apply a boolean mask to the batch object.
Truevalues are kept,Falsevalues are discarded- Parameters:
mask (ndarray[tuple[Any, ...], dtype[bool]]) – The boolean mask to apply to the object. Must be of size (num_masks, )
- Return type:
None
- append(mask_batch: ExtractBatchMask) None
Append the given mask batch object to this batch mask object
- Parameters:
mask_batch (ExtractBatchMask) – The object containing data to be appended to this object
- Return type:
None
- apply_mask(mask: ndarray[tuple[Any, ...], dtype[bool]]) None
Apply a boolean mask to the batch object.
Truevalues are kept,Falsevalues are discarded- Parameters:
mask (ndarray[tuple[Any, ...], dtype[bool]]) – The boolean mask to apply to the object. Must be of size (num_masks, )
- Return type:
None
- centering: CenteringType = <dataclasses._MISSING_TYPE object>
The centering type of the masks
- masks: npt.NDArray[np.uint8] = <dataclasses._MISSING_TYPE object>
The masks for this batch
- matrices: npt.NDArray[np.float32] = <dataclasses._MISSING_TYPE object>
The normalized matrices required to take the masks from (0, 1) to full frame
- storage_size: int = 0
The pixel size to store the mask at in the alignments file