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Dog Food Convnext Tiny 224
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Dog Food Convnext Tiny 224

Developed by sasha
This model is an image classification model based on the ConvNeXt-Tiny architecture, trained on the Dogs vs Food dataset, specifically designed to distinguish between images of dogs and food.
Image Classification
Transformers
#Pet Food Classification#ConvNeXt Architecture#High-Precision Image Recognition
Downloads 14
Release Time : 6/21/2022

Model Overview

This is an image classification model based on the ConvNeXt-Tiny architecture, trained on the Dogs vs Food dataset, capable of accurately distinguishing between images of dogs and food.

Model Features

High Accuracy
Achieved 100% accuracy on the test dataset.
Lightweight Architecture
Uses the ConvNeXt-Tiny architecture, suitable for resource-limited environments.
Easy to Use
Can be easily trained and deployed via HuggingPics.

Model Capabilities

Image Classification
Distinguishing Dogs and Food

Use Cases

Pet-Related Applications
Pet Food Recognition
Automatically identifies whether an image contains a pet dog or food.
100% accuracy
Smart Feeding System
Combines with a camera to identify whether a pet is in the feeding area.
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