tlc.core.builtins.types.segmentation_helper

Module Contents

Classes

Class

Description

SegmentationHelper

Helper class for segmentation operations.

API

class tlc.core.builtins.types.segmentation_helper.SegmentationHelper

Helper class for segmentation operations.

static empty_rle(height: int, width: int) → tlc.client.data_format.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_rle(rle: dict[str, list[int] | bytes]) → numpy.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[tlc.client.data_format.CocoRle]) → numpy.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 mask_from_polygons(polygons: list[list[float]], height: int, width: int, relative: bool = False) → numpy.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 polygons_from_mask(mask: numpy.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[tlc.client.data_format.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_polygons(polygons: list[list[float]], height: int, width: int, relative: bool = False) → list[tlc.client.data_format.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

static rles_from_masks(masks: numpy.ndarray) → list[tlc.client.data_format.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 bbox_from_rle(rle: tlc.client.data_format.CocoRle) → list[float]

Convert an RLE mask to a bounding box.

Parameters:

rle – The RLE mask to convert

Returns:

A list of bounding box coordinates [x1, y1, x2, y2]