## vit-base-blur Open-Source Model - Free Deployment for Distinguishing Blurry and Clear Images, Extremely Practical!

Vit Base Blur

Developed by WT-MM

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on a blurry image dataset, designed to distinguish between blurry and clear images.

Image Classification

Transformers

Open Source License:Apache-2.0 #Blurry Image Detection #High-Precision Classification #Diffusion Model Evaluation

Downloads 92

Release Time : 7/5/2023

Model Overview

This model is used for binary classification tasks, differentiating between 'noisy' (blurry) images and clear images, where 'noisy' images are the result of incomplete or insufficient iterations during image generation by LDM (Latent Diffusion Model).

Model Features

High Accuracy

Achieved an accuracy of 1.0 on the evaluation set, effectively distinguishing between blurry and clear images.

Based on ViT Architecture

Utilizes the Vision Transformer (ViT) architecture, offering robust image processing capabilities.

Few-Shot Fine-Tuning

Achieves excellent performance with fine-tuning on only about 1,000 images.

Model Capabilities

Image Classification

Blurry Image Detection

Binary Classification Task

Use Cases

Image Quality Detection

Generated Image Quality Assessment

Used to evaluate whether images generated by LDM reach sufficient clarity.

Accurately distinguishes between images generated with 30 steps and 10 steps.

Image Preprocessing

Automatic Blurry Image Filtering

Automatically identifies and filters low-quality images in image processing pipelines.

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0082	1.02	100	0.0107	1.0
0.0079	2.04	200	0.0052	1.0
0.0029	3.06	300	0.0028	1.0
0.002	4.08	400	0.0020	1.0
0.0016	5.1	500	0.0015	1.0
0.0013	6.12	600	0.0013	1.0
0.0011	7.14	700	0.0011	1.0
0.001	8.16	800	0.0010	1.0
0.0009	9.18	900	0.0009	1.0
0.0008	10.2	1000	0.0008	1.0
0.0008	11.22	1100	0.0008	1.0

Property	Details
Model Type	vit - base - blur
Training Data	blurry images dataset (imagefolder)
Task	Image Classification
Metrics	Accuracy (value: 1.0)

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Vit Base Blur

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