An executor that performs image segmentation on fashion items

Last update: Mar 30, 2022

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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Releases(v1.0.0)

v1.0.0(Dec 8, 2021)
v1.0.0 - 08.12.2021

ClothingSegmenter initial version

Added

U2NET implementation

Executor implementation

CI/CD

Source code(tar.gz)
Source code(zip)

An executor that performs image segmentation on fashion items

Related tags

Overview

ClothingSegmenter

Overview

References

Usage

via Docker image (recommended)

via source code

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Releases(v1.0.0)

v1.0.0(Dec 8, 2021)

v1.0.0 - 08.12.2021

Added

Owner

Jina AI

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`v1.0.0 - 08.12.2021`