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Segformer B3 Fashion

Developed by sayeed99
A fashion item image segmentation model based on SegFormer architecture, specifically designed for identifying and segmenting clothing and accessories
Downloads 75.65k
Release Time : 5/7/2024

Model Overview

This model is an image segmentation model fine-tuned on the fashion_segmentation dataset based on the nvidia/mit-b3 pre-trained model, capable of accurately identifying and segmenting various fashion items and clothing details in images.

Model Features

Fine-grained fashion item segmentation
Capable of identifying and segmenting 46 different fashion items and clothing details, including garments, accessories, and decorative elements
Original size processing
Uses original image dimensions during training without resizing, preserving more detail information
Transformer-based architecture
Utilizes the advanced SegFormer architecture, combining the advantages of Transformer with efficient design

Model Capabilities

Clothing image segmentation
Fashion item recognition
Clothing detail detection
Multi-category semantic segmentation

Use Cases

Fashion e-commerce
Product auto-tagging
Automatically identify and tag various components in clothing product images on e-commerce platforms
Improves product tagging efficiency and reduces manual workload
Virtual try-on
Provides foundational support for virtual try-on systems through precise clothing area segmentation
Enhances user experience and try-on effects
Fashion analysis
Trend analysis
Automatically identify clothing types and styles in street photos or social media images
Assists in fashion trend analysis and prediction
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