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---
task_categories:
- image-classification
language:
- en
tags:
- Images
pretty_name: 'Material Classification Hands On '
size_categories:
- n<1K
dataset_info:
config_name: plain_text
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Brick
'1': Metal
'2': Paper
'3': Plastic
'4': Wood
splits:
- name: train
num_examples: 120
- name: test
num_examples: 30
license: mit
---
# Dataset Card for Material Classification
## Dataset Description
- **Homepage:** https://semillerocv.github.io/proyectos.html
- **Repository:** https://github.com/Sneider-exe/Clasificacion_Materiales
### Dataset Summary
The Material_classification_2U dataset consists of 150 256x256 color images, categorized into 5 classes with 30 images per class. The dataset is divided into two main subsets: 120 images for training and 30 images for testing. Each image is labeled into one of the following five categories: Brick, Metal, Paper, Plastic, and Wood.
### Supported Tasks and Leaderboards
- `image-classification`: The goal of this task is to classify a given image into one of 5 classes.
### Languages
English
## Dataset Structure
### Dataset Structure
- **Total Images:** 150
- **Image Size:** 256x256 pixels
- **Color:** RGB (Color images)
- **Classes:** 5
- **Brick:** 30 images
- **Metal:** 30 images
- **Paper:** 30 images
- **Plastic:** 30 images
- **Wood:** 30 images
- **Splits:**
- **Train:** 120 images (24 per class)
- **Test:** 30 images (6 per class)
### Data Instances
A sample from the training set is provided below:
```
{
'image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=256x256>,
'label': 1
}
```
### Data Fields
- image: A `PIL.Image.Image` object containing the 256x256 image. Note that when accessing the image column: `dataset['train']["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time.
- label: 0-4 with the following correspondence
'0': Brick
'1': Metal
'2': Paper
'3': Plastic
'4': Wood
### Data Splits
Train and Test
### Citation Information
```
@TECHREPORT{
author = {Brayan Sneider Sánchez, Dana Meliza Villamizar, Cesar Vanegas, Juan Jose Calderón},
title = {Material Classification},
institution = {Universidad Industrial de Santander},
year = {2024}
}
``` |