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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.
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.
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