Open-source Image Classification Model for Cat vs Dog Classification - Free Deployment to Accurately Distinguish Cat and Dog Images

Cat Vs Dog Classification

Developed by kazuma313

An image classification model fine-tuned on the cats_vs_dogs dataset using Google's ViT model, designed to distinguish between images of cats and dogs.

Image Classification

Transformers

Open Source License:Apache-2.0 #High-precision image classification #Pet recognition #ViT fine-tuned model

Downloads 42

Release Time : 2/26/2024

Model Overview

This model is an image classifier based on the Vision Transformer (ViT) architecture, specifically designed to differentiate between pictures of cats and dogs. It achieved an accuracy of 99.44% on the evaluation set.

Model Features

High Accuracy

Achieved a classification accuracy of 99.44% on the evaluation set.

Based on ViT Architecture

Utilizes the Vision Transformer architecture, suitable for image classification tasks.

Fast Inference

Can process approximately 61 images per second, making it suitable for real-time applications.

Model Capabilities

Image classification

Cat and dog recognition

Use Cases

Pet-related applications

Automatic pet photo classification

Automatically identifies and classifies user-uploaded photos of cats and dogs.

99.44% accuracy

Smart pet monitoring

Identifies cats or dogs in surveillance system footage.

Property	Details
Model Type	Fine - tuned version of google/vit - base - patch16 - 224 - in21k
Training Data	cats_vs_dogs

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Cat Vs Dog Classification

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 cat_vs_dog_classification

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📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

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