Manipulate run-length-encoded image masks
Project description
RLEMaskLib: Run-Length Encoded Mask Operations
Fast run-length encoded (RLE) binary mask operations in Python. Core implemented in C via Cython for efficiency.
The API is designed to feel like NumPy and OpenCV, with familiar slicing, boolean operators, and method names.
Fully compatible with the COCO mask format.
Installation
pip install rlemasklib
Quick Start
import numpy as np
from rlemasklib import RLEMask
# Create from numpy array
mask = RLEMask(np.array([
[0, 1, 1],
[1, 1, 0],
[0, 0, 1]
]))
# Boolean operations
union = mask1 | mask2
intersection = mask1 & mask2
difference = mask1 - mask2
complement = ~mask
# Morphology
eroded = mask.erode3x3()
dilated = mask.dilate3x3()
# Geometric transforms (NumPy/OpenCV style)
flipped = mask.fliplr()
rotated = mask.rot90()
cropped = mask[10:50, 20:80] # slicing like numpy
resized = mask.resize((256, 256))
# Analysis
area = mask.area()
bbox = mask.bbox()
components = mask.connected_components()
# COCO format I/O
coco_dict = mask.to_dict() # {'size': [h, w], 'counts': b'...'}
mask = RLEMask.from_dict(coco_dict)
Features
- Boolean operations: union, intersection, difference, complement, XOR, custom functions
- Morphology: erode, dilate, open, close (3x3, 5x5, arbitrary kernels)
- Geometric: crop, pad, tile, flip, transpose, rotate, resize, warp (affine/perspective)
- Analysis: area, bounding box, connected components, largest interior rectangle, IoU
- I/O: COCO format, numpy arrays, polygons, bounding boxes, circles
- Compression: LEB128 (COCO-compatible) + optional gzip (~40% smaller)
APIs
Object-oriented (recommended): Work with RLEMask objects for chained operations.
Functional (legacy): Dict-to-dict operations, compatible with COCO's pycocotools.mask.
Documentation
Full documentation with visual examples: rlemasklib.readthedocs.io
Origin
Fork of COCO API's pycocotools.mask (by Piotr Dollár and Tsung-Yi Lin), now mostly new code.
Project details
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