Wd Swinv2 Tagger V3 Hf
An image tag classification model based on the SwinV2 architecture for automatically identifying content and features in images
Downloads 8,969
Release Time : 3/8/2024
Model Overview
This is an image classification model based on the SwinV2 architecture, capable of automatically recognizing various elements and features in images, including objects, scenes, characters, etc., and outputting corresponding tags. The model is particularly suitable for anime/2D image analysis.
Model Features
High-precision Image Tag Recognition
Accurately identifies various elements in images, including characters, clothing, scenes, etc.
Support for Rating and Character Tags
Provides rating tags (rating:) and character tags (character:), facilitating content classification
Optimum Acceleration Support
Can be accelerated via ONNX Runtime, achieving a 30% speed boost and 50% model size reduction
Model Capabilities
Image Content Analysis
Automatic Tag Generation
Anime Image Recognition
Character Feature Recognition
Use Cases
Content Management
Automatic Image Tagging
Automatically generates descriptive tags for images in a library
Improves image retrieval and organization efficiency
Anime Analysis
Character Recognition
Identifies specific characters in anime images
Useful for fan content organization or copyright management
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