V

Vit Base Patch16 224 Blur Vs Clean

Developed by harrytechiz
A fine-tuned model based on Google's Vision Transformer (ViT) architecture, specifically designed for distinguishing between blurry and clear images
Downloads 1,542
Release Time : 11/24/2023

Model Overview

This model is fine-tuned from the google/vit-base-patch16-224 base model, specifically for image classification tasks, excelling particularly in distinguishing between blurry and clear images, achieving an accuracy of 97.54% on the evaluation set.

Model Features

High Accuracy
Achieves 97.54% accuracy in blurry vs clear image classification tasks
Based on ViT Architecture
Utilizes the Vision Transformer architecture with self-attention mechanisms for image processing
Transfer Learning
Fine-tuned from a pre-trained ViT model, effectively leveraging existing knowledge

Model Capabilities

Image Classification
Blur Detection
Image Quality Assessment

Use Cases

Image Processing
Image Quality Filtering
Automatically filters out blurry or low-quality images
97.54% accuracy
Photo Management
Helps users automatically categorize clear and blurry photos
Computer Vision
Preprocessing Filter
Prefilters low-quality images in computer vision pipelines
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