Image segmentation mask to polygon for coco json

7 min read 05-10-2024
Image segmentation mask to polygon for coco json


From Pixel Mask to Polygon: Converting COCO JSON Segmentation Masks for Efficient Object Detection

The Problem:

COCO datasets use a versatile format, including segmentation masks defined by pixel values. However, working with these masks for object detection can be computationally expensive. Converting them to polygon representations can significantly improve efficiency and reduce memory usage, especially for complex objects with intricate boundaries.

Understanding the Need:

Imagine analyzing a scene with dozens of intricate objects. If each object is defined by a detailed pixel mask, processing and analyzing this data becomes computationally demanding. Polygon representations offer a more compact and efficient alternative.

Example:

Let's say we have a COCO JSON file containing an image of a cat. Its segmentation mask, represented as a pixel array, might look like this:

{
  "segmentation": [
    [
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