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  - name: train
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  num_examples: 120
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  - name: test
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- num_examples: 30¿
 
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  ---
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  # Dataset Card for Material Classification
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- ## Table of Contents
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- - [Dataset Description](#dataset-description)
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- - [Dataset Summary](#dataset-summary)
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- - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- - [Languages](#languages)
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- - [Dataset Structure](#dataset-structure)
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- - [Data Instances](#data-instances)
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- - [Data Fields](#data-fields)
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- - [Data Splits](#data-splits)
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- - [Dataset Creation](#dataset-creation)
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- - [Curation Rationale](#curation-rationale)
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- - [Source Data](#source-data)
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- - [Annotations](#annotations)
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- - [Personal and Sensitive Information](#personal-and-sensitive-information)
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- - [Considerations for Using the Data](#considerations-for-using-the-data)
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- - [Social Impact of Dataset](#social-impact-of-dataset)
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- - [Discussion of Biases](#discussion-of-biases)
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- - [Other Known Limitations](#other-known-limitations)
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- - [Additional Information](#additional-information)
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- - [Dataset Curators](#dataset-curators)
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- - [Licensing Information](#licensing-information)
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- - [Citation Information](#citation-information)
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- - [Contributions](#contributions)
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  ## Dataset Description
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  - **Homepage:** https://semillerocv.github.io/proyectos.html
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- - **Repository:**
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- - **Paper:**
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- - **Leaderboard:**
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- - **Point of Contact:**
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  ### Dataset Summary
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- The Material_classification_2U dataset consists of 150 256x256 colour images in 5 classes, with 30 images per class. There are 120 training images and 30 test images.
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  ### Supported Tasks and Leaderboards
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  - `image-classification`: The goal of this task is to classify a given image into one of 5 classes.
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  English
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  ## Dataset Structure
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Data Instances
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  Train and Test
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- ## Dataset Creation
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- ### Curation Rationale
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- [More Information Needed]
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- ### Source Data
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- #### Initial Data Collection and Normalization
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- [More Information Needed]
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- #### Who are the source language producers?
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- [More Information Needed]
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- ### Annotations
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- #### Annotation process
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- [More Information Needed]
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- #### Who are the annotators?
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- [More Information Needed]
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- ### Personal and Sensitive Information
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- [More Information Needed]
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- ## Considerations for Using the Data
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- ### Social Impact of Dataset
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- [More Information Needed]
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- ### Discussion of Biases
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- [More Information Needed]
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- ### Other Known Limitations
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- [More Information Needed]
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- ## Additional Information
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- ### Dataset Curators
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- [More Information Needed]
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- ### Licensing Information
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- [More Information Needed]
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  ### Citation Information
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  - name: train
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  num_examples: 120
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  - name: test
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+ num_examples: 30
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+ license: mit
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  ---
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  # Dataset Card for Material Classification
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  ## Dataset Description
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  - **Homepage:** https://semillerocv.github.io/proyectos.html
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+ - **Repository:** https://github.com/Sneider-exe/Clasificacion_Materiales
 
 
 
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  ### Dataset Summary
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+ 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.
 
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  ### Supported Tasks and Leaderboards
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  - `image-classification`: The goal of this task is to classify a given image into one of 5 classes.
 
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  ## Dataset Structure
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+ ### Dataset Structure
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+ - **Total Images:** 150
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+ - **Image Size:** 256x256 pixels
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+ - **Color:** RGB (Color images)
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+ - **Classes:** 5
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+ - **Brick:** 30 images
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+ - **Metal:** 30 images
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+ - **Paper:** 30 images
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+ - **Plastic:** 30 images
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+ - **Wood:** 30 images
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+ - **Splits:**
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+ - **Train:** 120 images (24 per class)
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+ - **Test:** 30 images (6 per class)
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  ### Data Instances
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  Train and Test
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  ### Citation Information
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