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README.md
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---
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dataset_info:
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features:
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- name: image
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dtype: image
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'4': Wood
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splits:
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- name: train
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num_bytes: 16618897.4
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num_examples: 120
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- name: test
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-
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num_examples: 30
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download_size: 20778905
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dataset_size: 20773623.0
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: test
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path: data/test-*
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---
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---
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task_categories:
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- image-classification
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language:
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- en
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tags:
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- Images
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pretty_name: 'Material Classification Hands On '
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size_categories:
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- n<1K
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dataset_info:
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config_name: plain_text
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features:
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- name: image
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dtype: image
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'4': Wood
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splits:
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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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### Languages
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English
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## Dataset Structure
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### Data Instances
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A sample from the training set is provided below:
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```
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{
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'image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=256x256>,
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'label': 1
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}
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```
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### Data Fields
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- 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.
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- label: 0-4 with the following correspondence
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'0': Brick
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'1': Metal
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'2': Paper
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'3': Plastic
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'4': Wood
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### Data Splits
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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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```
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@TECHREPORT{
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author = {Brayan Sneider Sánchez, Dana Meliza Villamizar, Cesar Vanegas, Juan Jose Calderón},
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title = {Material Classification},
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institution = {Universidad Industrial de Santander},
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year = {2024}
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}
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```
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