francbianc/clothing_instance_segmentation
A supervised Deep Learning approach to clothing instance segmentation with Mask R-CNN
This project helps fashion retailers, e-commerce managers, or social media analysts automatically identify and outline individual clothing items in real-world photos, especially those from social media like Instagram. You provide unstructured images of people wearing clothes, and it outputs precise digital masks around each of 30 specific fashion items (like 'dress', 'jeans', 'hat'), separating them from the background and other items. This is useful for cataloging, trend analysis, or visual search.
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Use this if you need to precisely locate and segment individual clothing items within "in the wild" images, such as user-generated content or lifestyle photos, rather than studio-quality pictures.
Not ideal if your primary need is general object detection or if you only work with highly controlled, clean images where backgrounds are uniform and items are clearly separated.
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MIT
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Last pushed
Mar 17, 2022
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