--- annotations_creators: - machine-generated language_creators: - machine-generated language: - en license: - other multilinguality: - monolingual pretty_name: Object Detection for Chess Pieces size_categories: - n<1K source_datasets: [] task_categories: - object-detection task_ids: [] --- # Dataset Card for Object Detection for Chess Pieces ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-instances) - [Data Splits](#data-instances) - [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) ## Dataset Description - **Homepage:** https://github.com/faizankshaikh/chessDetection - **Repository:** https://github.com/faizankshaikh/chessDetection - **Paper:** - - **Leaderboard:** - - **Point of Contact:** [Faizan Shaikh](mailto:faizankshaikh@gmail.com) ### Dataset Summary 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 ### Supported Tasks and Leaderboards - `object-detection`: The dataset can be used to train and evaluate simplistic object detection models ### Languages The text (labels) in the dataset is in English ## Dataset Structure ### Data Instances A data point comprises an image and the corresponding objects in bounding boxes. ``` { 'image': , 'objects': { "label": [ 0 ], "bbox": [ [ 151, 151, 26, 26 ] ] } } ``` ### Data Fields - `image`: A `PIL.Image.Image` object containing the 224x224 image. - `label`: An integer between 0 and 3 representing the classes with the following mapping: | Label | Description | | --- | --- | | 0 | blackKing | | 1 | blackQueen | | 2 | whiteKing | | 3 | whiteQueen | - `bbox`: A list of integers having sequence [x_center, y_center, width, height] for a particular bounding box ### Data Splits The data is split into training and validation set. The training set contains 204 images and the validation set 52 images. ## Dataset Creation ### Curation Rationale The dataset was created to be a simple benchmark for object detection ### Source Data #### Initial Data Collection and Normalization 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 #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process The annotations were done manually. #### Who are the annotators? The annotations were done manually. ### Personal and Sensitive Information None ## Considerations for Using the Data ### Social Impact of Dataset 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. ### Discussion of Biases [Needs More Information] ### Other Known Limitations 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 ## Additional Information ### Dataset Curators The dataset was created by Faizan Shaikh ### Licensing Information The dataset is licensed as CC-BY-SA:2.0 ### Citation Information [Needs More Information]