https://github.com/priyapuranik/shoe-classification_using-cnn

A deep learning project that classifies different types of shoes using Convolutional Neural Networks (CNNs) based on image data.
https://github.com/priyapuranik/shoe-classification_using-cnn

cv2 deep-learning keras matplotlib-pyplot python tensorflow

Last synced: 15 days ago
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A deep learning project that classifies different types of shoes using Convolutional Neural Networks (CNNs) based on image data.

• Host: GitHub
• URL: https://github.com/priyapuranik/shoe-classification_using-cnn
• Owner: priyapuranik
• Created: 2024-08-31T12:12:31.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-10-23T16:55:19.000Z (15 days ago)
• Last Synced: 2024-10-23T23:43:20.592Z (15 days ago)
• Topics: cv2, deep-learning, keras, matplotlib-pyplot, python, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 38.1 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# CNN_Shoe_Classification

## Overview

This project aims to classify different types of shoes using Convolutional Neural Networks (CNNs). The model is trained on a dataset of shoe images and is designed to accurately identify various shoe categories.


**--The model classifies images of three types of footwear: boots, sandals, and slippers.**


**--Achieved an overall accuracy of 91% on the test set.**


**--Precision, recall, and F1-scores for each class are as follows:**


*Boots (0): Precision = 97%, Recall = 97%, F1-Score = 97%.*


*Sandals (1): Precision = 86%, Recall = 92%, F1-Score = 89%.*


*Slippers (2): Precision = 90%, Recall = 79%, F1-Score = 84%.*


**The model was trained and tested on a dataset of 156 images, with balanced precision and recall for most classes.**


***The purpose of this project is to develop a deep learning model capable of classifying different types of footwear, which can be used in e-commerce platforms or retail applications to automatically tag and categorize footwear images.***