Open-source food image classification model - Trained on Food101, with an accurate food recognition rate of nearly 88.31%

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Food Image Classification

Developed by Shresthadev403

Food image classification model trained on the Food101 dataset with an accuracy of 88.31%

Image Classification

Transformers

#Food Image Recognition #High Accuracy Classification #Catering Industry Application

Downloads 531

Release Time : 2/4/2024

Model Overview

This model is a vision model for food image classification, capable of recognizing 101 categories of food included in the Food101 dataset.

Model Features

High Accuracy

Achieves a classification accuracy of 88.31% on the Food101 evaluation set

Efficient Inference

Can process 96.74 samples per second, suitable for real-time applications

Fine-grained Classification

Capable of recognizing 101 different categories of food

Model Capabilities

Food Image Classification

Multi-category Recognition

Use Cases

Catering Industry

Smart Menu Recognition

Used in restaurants to automatically identify photos of dishes taken by customers

Can quickly and accurately identify dish categories

Food Logging Application

Helps users record daily dietary content

Automatically identifies and classifies food photos taken by users

Health Management

Diet Analysis

Analyzes users' eating habits and nutritional intake

Provides dietary advice through food classification

Property	Details
Model Type	food-image-classification
Training Data	food101

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Food Image Classification

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🚀 Food Image Classification

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