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Vit Artworkclassifier

Developed by oschamp
Art style classification model based on ViT architecture, capable of identifying the art style category of input images
Downloads 41
Release Time : 2/21/2023

Model Overview

This model is an art style classifier fine-tuned on the artbench-10 dataset using Google's ViT-base-patch16-224-in21k, capable of recognizing 9 different art styles

Model Features

Art Style Recognition
Accurately identifies the art style category of input images
Efficient Fine-tuning
Achieves good results with limited data through efficient fine-tuning based on a pre-trained ViT model
Multi-category Classification
Supports classification and recognition of 9 different art styles

Model Capabilities

Image Classification
Art Style Recognition
Visual Feature Extraction

Use Cases

Art Analysis
Artwork Classification
Automatically classifies the styles of works in digital art collections
Accuracy reaches 59.48%
Art Education
Assists art learners in identifying works of different art styles
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