Footwear-Shoe vs Sandal vs Boot Image Dataset (3K)

Dataset Overview

The Footwear Image Dataset provides a comprehensive collection of 9,000 labeled images spanning three categories: shoes, sandals, and boots. Each category contains 3,000 images in RGB color format with a resolution of 136×102 pixels, making it ideal for training and testing computer vision and machine learning models.

This dataset is optimized for tasks such as multiclass image classification, deep learning, and pattern recognition, making it a valuable resource for researchers and developers in the fields of AI, fashion technology, and e-commerce.

Dataset Highlights

1. Image Categories:

   • Shoes: Everyday footwear for casual or formal wear.
   • Sandals: Open-toe footwear suitable for warmer climates.
   • Boots: Durable footwear for outdoor and cold-weather use.

2. Resolution:

   • All images are resized to 136×102 pixels, providing consistency for model training.

3. Color Model:

   • Images are in the RGB color model, capturing vibrant and accurate visual details.

4. Usability:

   • Ideal for multiclass classification using Convolutional Neural Networks (CNNs) and other machine learning models.

This dataset is sourced from Kaggle.