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README.md

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-# Dataset Card for Dataset Name
-
-<!-- Provide a quick summary of the dataset. -->
-
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
+# Dataset Card for LEGO Visual Tasks Dataset
 
 ## Dataset Details
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
-
-
+The LEGO Visual Tasks Dataset is designed for research in visual perspective taking (VPT), scene understanding, and spatial reasoning. It contains 144 visual tasks inspired by human VPT tests, such as those detailed in O'Grady et al. (2020) and Lukosiunaite et al. (2024). Each task involves a minifigure-object pair created using LEGO components and systematically photographed in varying spatial arrangements and orientations. 
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
+This dataset can be utilized for evaluating models’ abilities in object recognition, spatial reasoning, and perspective-taking, making it a valuable resource for studies in artificial intelligence, cognitive science, and computer vision.
 
-### Dataset Sources [optional]
+### Dataset Sources
 
-<!-- Provide the basic links for the dataset. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [https://github.com/GracjanGoral/ISLE]
+- **Paper:** [https://arxiv.org/abs/2409.12969]
 
 ## Uses
 
-<!-- Address questions around how the dataset is intended to be used. -->
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 ### Direct Use
 
-<!-- This section describes suitable use cases for the dataset. -->
-
-[More Information Needed]
+The dataset is suitable for:
+- Training and evaluating models in visual perspective-taking tasks.
+- Studying scene understanding, spatial reasoning, and object recognition.
+- Testing abilities to answer diagnostic questions related to the dataset's scenarios.
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
+The dataset should not be used for:
+- Malicious purposes such as creating misleading or biased AI applications.
+- Tasks unrelated to the intended goals of visual reasoning and perspective-taking.
 
 ## Dataset Structure
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+The dataset consists of:
 
-[More Information Needed]
+- **Images:** Photographs of nine unique LEGO minifigure-object pairs systematically varied by:
+  - **Spatial Position:** Object relative to the minifigure’s left, right, behind, or in front.
+  - **Minifigure Orientation:** Facing toward or away from the object.
+  - **Camera Viewpoints:** Bird’s-eye view and surface-level view.
+  - **Image Resolution:** Each image has 4000 x 3000 pixels.
+
+- **Metadata File:** A structured file containing:
+  - `image_id`: Unique identifier for each image.
+  - `question_1` to `question_7`: Questions testing scene understanding, spatial reasoning, and visual perspective-taking.
+  - `gold_answer`: The correct answer for each question.
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
+This dataset was created to systematically test visual reasoning models on tasks inspired by human cognitive processes. It aims to bridge the gap between machine learning performance and human abilities in tasks requiring scene understanding, spatial reasoning, and perspective-taking.
 
 ### Source Data
 
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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 #### Data Collection and Processing
 
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
+The images were collected by:
+- Designing nine unique minifigure-object pairs using LEGO pieces.
+- Systematically varying spatial positions, orientations, and camera angles for each pair.
+- Photographing each arrangement with consistent lighting and surface conditions.
+- The images were manually created, and each has a resolution of 4000 x 3000 pixels.
 
 #### Who are the source data producers?
 
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
-#### Annotation process
+The source data producers include the dataset creator Gracjan Goral, who designed the LEGO minifigure-object pairs and performed systematic photography.
 
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
+### Annotations
 
-[More Information Needed]
+#### Annotation Process
 
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
+- Three annotators labeled data, and the gold answers were produced by majority choice among the annotators.
+- The labeling process achieved over 99% agreement among annotators
 
 #### Personal and Sensitive Information
 
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
+The dataset does not contain any personal, sensitive, or private information. All data consists of LEGO objects and metadata derived from the tasks.
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+Users should consider the following:
+- The dataset is limited to synthetic scenes involving LEGO components and may not generalize to real-world scenarios.
+- 
+## Citation
 
 **BibTeX:**
+@dataset{LEGO_Visual_Tasks, author = {Gracjan Goral}, title = {LEGO Visual Tasks Dataset}, year = {2025}, publisher = {Hugging Face}, note = {https://huggingface.co/datasets/lego_visual_tasks}, howpublished = {Used in article: https://arxiv.org/abs/2409.12969} }
 
-[More Information Needed]
 
 **APA:**
+Goral, G. (2025). LEGO Visual Tasks Dataset. Available at https://huggingface.co/datasets/lego_visual_tasks. Used in article: https://arxiv.org/abs/2409.12969.
 
-[More Information Needed]
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-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
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-## More Information [optional]
-
-[More Information Needed]
-
-## Dataset Card Authors [optional]
-
-[More Information Needed]
-
-## Dataset Card Contact
+## Glossary
 
-[More Information Needed]
+- **VPT (Visual Perspective Taking):** The ability to interpret a scene from another entity’s perspective.
+- **Object Recognition:** Identifying and counting objects within a scene.
+- **Spatial Reasoning:** Understanding spatial relationships and orientations.