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Fastfood Classifier
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Fastfood Classifier

Developed by AryanKaushik
An image classification model based on PyTorch framework and generated by HuggingPics tool, specifically designed for identifying common fast food items.
Image Classification
TensorBoard
#High-precision food recognition#Fast food image classification#AI applications in catering industry
Downloads 46
Release Time : 2/21/2025

Model Overview

This model can classify images of common fast food items (such as hamburgers, pizza, fries, etc.) with an accuracy rate of 86.49%.

Model Features

High accuracy
Achieves 86.49% accuracy in fast food classification tasks
Ease of use
Automatically generated via HuggingPics tool for quick deployment and usage
Multi-category recognition
Supports classification of various fast food items including hamburgers, pizza, fries, waffles, etc.

Model Capabilities

Image classification
Fast food recognition
Food classification

Use Cases

Catering industry
Fast food restaurant automated ordering system
Automatically identifies food types by taking pictures of meals
Improves ordering efficiency and accuracy
Food inventory management
Automatically identifies and categorizes food items in inventory
Simplifies inventory management process
Health management
Diet tracking application
Automatically identifies types of fast food consumed by users
Helps users track dietary habits
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