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Datasets:
SemilleroCV
/
BWMP2

Tasks:
Image Classification
Modalities:
Image
Formats:
parquet
Languages:
English
Size:
< 1K
Tags:
Images
DOI:
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
1
BWMP2
File size: 3,774 Bytes 
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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¿
---
# Dataset Card for Material Classification

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://semillerocv.github.io/proyectos.html
- **Repository:** 
- **Paper:** 
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

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.

### 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

### 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

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### 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}
}
```