An executor that performs image segmentation on fashion items

Related tags

Deep Learning executor-image-clothing-segmenter
Overview

ClothingSegmenter

U2NET fashion image/clothing segmenter based on https://github.com/levindabhi/cloth-segmentation

Overview

The ClothingSegmenter executor can be used to perform segmentation on images of fashion products. The executor is based on a U2NET architecture pre-trained on iMaterialistic fashion 2019. The parts of the image that represent clothing or fashion items are recognized, using the U2NET pixel-wise segmentation model and the rest of the image content is filtered out. Images that pass through the executor are resized to a fixed shape of (500, 768) to match the pre-training image size.

References

Usage

via Docker image (recommended)

from jina import Flow
	
f = Flow().add(uses='jinahub+docker://ClothingSegmenter')

via source code

from jina import Flow
	
f = Flow().add(uses='jinahub://ClothingSegmenter')
  • To override __init__ args & kwargs, use .add(..., uses_with: {'key': 'value'})
  • To override class metas, use .add(..., uses_metas: {'key': 'value})
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