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--- |
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annotations_creators: |
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- machine-generated |
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language_creators: |
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- machine-generated |
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language: |
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- en |
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license: |
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- other |
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multilinguality: |
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- monolingual |
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pretty_name: Object Detection for Chess Pieces |
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size_categories: |
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- n<1K |
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source_datasets: [] |
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task_categories: |
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- object-detection |
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task_ids: [] |
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--- |
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# Dataset Card for Object Detection for Chess Pieces |
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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](#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-instances) |
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- [Data Splits](#data-instances) |
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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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## Dataset Description |
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- **Homepage:** https://github.com/faizankshaikh/chessDetection |
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- **Repository:** https://github.com/faizankshaikh/chessDetection |
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- **Paper:** - |
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- **Leaderboard:** - |
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- **Point of Contact:** [Faizan Shaikh](mailto:faizankshaikh@gmail.com) |
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### Dataset Summary |
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The "Object Detection for Chess Pieces" dataset is a toy dataset created (as suggested by the name!) to introduce object detection in a beginner friendly way. It is structured in a one object-one image manner, with the objects being of four classes, namely, Black King, White King, Black Queen and White Queen |
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### Supported Tasks and Leaderboards |
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- `object-detection`: The dataset can be used to train and evaluate simplistic object detection models |
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### Languages |
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The text (labels) in the dataset is in English |
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## Dataset Structure |
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### Data Instances |
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A data point comprises an image and the corresponding objects in bounding boxes. |
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``` |
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{ |
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'image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=224x224 at 0x23557C66160>, |
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'objects': { "label": [ 0 ], "bbox": [ [ 151, 151, 26, 26 ] ] } |
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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 224x224 image. |
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- `label`: An integer between 0 and 3 representing the classes with the following mapping: |
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| Label | Description | |
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| --- | --- | |
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| 0 | blackKing | |
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| 1 | blackQueen | |
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| 2 | whiteKing | |
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| 3 | whiteQueen | |
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- `bbox`: A list of integers having sequence [x_center, y_center, width, height] for a particular bounding box |
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### Data Splits |
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The data is split into training and validation set. The training set contains 204 images and the validation set 52 images. |
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## Dataset Creation |
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### Curation Rationale |
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The dataset was created to be a simple benchmark for object detection |
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### Source Data |
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#### Initial Data Collection and Normalization |
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The data is obtained by machine generating images from "python-chess" library. Please refer [this code](https://github.com/faizankshaikh/chessDetection/blob/main/code/1.1%20create_images_with_labels.ipynb) to understand data generation pipeline |
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#### Who are the source language producers? |
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[Needs More Information] |
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### Annotations |
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#### Annotation process |
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The annotations were done manually. |
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#### Who are the annotators? |
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The annotations were done manually. |
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### Personal and Sensitive Information |
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None |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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The dataset can be considered as a beginner-friendly toy dataset for object detection. It should not be used for benchmarking state of the art object detection models, or be used for a deployed model. |
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### Discussion of Biases |
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[Needs More Information] |
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### Other Known Limitations |
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The dataset only contains four classes for simplicity. The complexity can be increased by considering all types of chess pieces, and by making it a multi-object detection problem |
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## Additional Information |
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### Dataset Curators |
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The dataset was created by Faizan Shaikh |
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### Licensing Information |
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The dataset is licensed as CC-BY-SA:2.0 |
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### Citation Information |
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[Needs More Information] |
