tlc.helpers.segmentation_helper¶

Helpers for working with segmentation data, including RLE and polygon conversion.

Module Contents¶

Classes¶

Class

Description

SegmentationHelper

Helper class for segmentation operations.

API¶

class SegmentationHelper¶

Helper class for segmentation operations.

static bounding_box_from_rle(
rle: CocoRle,
) → list[float]¶

Convert an RLE mask to a bounding box.

Parameters:

rle – The RLE mask to convert

Returns:

The tight bounding box around the mask in COCO [x, y, width, height] format, where (x, y) is the top-left corner in absolute pixels.

static empty_rle(
height: int,
width: int,
) → CocoRle¶

Create an empty RLE mask with the given dimensions.

Parameters:

  • height – Height of the mask

  • width – Width of the mask

Returns:

An empty RLE mask dictionary with ‘counts’ and ‘size’ fields

static mask_from_polygons(
polygons: list[list[float]],
height: int,
width: int,
*,
relative: bool = False,
) → ndarray¶

Convert a list of polygons to a numpy array.

Parameters:

  • polygons – The list of polygons to convert

  • height – The height of the image

  • width – The width of the image

  • relative – Whether the polygons are relative to the image size

Returns:

A numpy array of shape (H, W, N) containing N binary masks

static mask_from_rle(
rle: dict[str, list[int] | bytes],
) → ndarray¶

Convert an RLE mask to a numpy array.

Parameters:

rle – The RLE mask to convert

Returns:

A numpy array of shape (H, W, N) containing N binary masks

static masks_from_rles(
rles: list[CocoRle],
) → ndarray¶

Convert multiple RLE masks to a numpy array.

Parameters:

rles – List of RLE dictionaries with ‘counts’ and ‘size’ fields

Returns:

A numpy array of shape (H, W, N) containing N binary masks

static polygons_from_mask(
mask: ndarray,
*,
relative: bool = False,
) → list[float]¶

Convert a binary mask to a list of polygons using OpenCV contour detection.

Parameters:

  • mask – The binary mask to convert

  • relative – Whether to return polygons with coordinates relative to image dimensions

Returns:

List of polygons where each polygon is a flattened list of x,y coordinates

static polygons_from_rles(
rles: list[CocoRle],
*,
relative: bool = False,
) → list[list[float]]¶

Convert a list of RLE encoded masks to polygons.

Parameters:

  • rles – List of RLE dictionaries with ‘counts’ and ‘size’ fields

  • relative – Whether to return polygons with coordinates relative to image dimensions

Returns:

List of polygons where each polygon is a flattened list of x,y coordinates

static rles_from_masks(
masks: ndarray,
) → list[CocoRle]¶

Convert a stack of binary masks to RLE format.

Parameters:

masks – A numpy array of shape (H, W, N) containing N binary masks

Returns:

List of RLE dictionaries with ‘counts’ and ‘size’ fields

static rles_from_polygons(
polygons: list[list[float]],
height: int,
width: int,
*,
relative: bool = False,
) → list[CocoRle]¶

Convert a list of polygons to RLE format.

Parameters:

  • polygons – The list of polygons to convert

  • height – The height of the image

  • width – The width of the image

  • relative – Whether the polygons are relative to the image size

Returns:

List of RLE dictionaries with ‘counts’ and ‘size’ fields