# Dataset Card for Sketch Data Model Dataset

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks](#supported-tasks-and-leaderboards)
- [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/sketchai
- **Repository:** https://github.com/sketchai/preprocessing
- **Paper:** [Needs More Information]
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** [Needs More Information]

### Dataset Summary

This dataset contains over 6M CAD 2D sketches extracted from Onshape. Sketches are stored as python objects in the custom SAM format.
SAM leverages the [Sketchgraphs](https://github.com/PrincetonLIPS/SketchGraphs) dataset for industrial needs and allows for easier transfer learning on other CAD softwares.

### Supported Tasks and Leaderboards

Tasks: Automatic Sketch Generation, Auto Constraint

## Dataset Structure

### Data Instances

The presented npy files contain python pickled objects and require the [flat_array](https://github.com/PrincetonLIPS/SketchGraphs/blob/master/sketchgraphs/data/flat_array.py) module of Sketchgraphs to be loaded. The normalization_output_merged.npy file contains sketch sequences represented as a list of SAM Primitives and Constraints. The sg_merged_final_*.npy files contain encoded constraint graphs of the sketches represented as a dictionnary of arrays.

### Data Fields

[Needs More Information]

### Data Splits
|Train |Val   |Test  |
|------|------|------|
|6M    |50k   | 50k  |

## Dataset Creation

### Curation Rationale

[Needs More Information]

### Source Data

#### Initial Data Collection and Normalization

[Needs More Information]

#### Who are the source language producers?

[Needs More Information]

### Annotations

#### Annotation process

[Needs More Information]

#### Who are the annotators?

[Needs More Information]

### Personal and Sensitive Information

[Needs More Information]

## Considerations for Using the Data

### Social Impact of Dataset

[Needs More Information]

### Discussion of Biases

[Needs More Information]

### Other Known Limitations

[Needs More Information]

## Additional Information

### Dataset Curators

[Needs More Information]

### Licensing Information

[Needs More Information]

### Citation Information

[Needs More Information]
annotations_creators:no-annotation language_creators:other size_categories:1M<n<10M license:lgpl-3.0 region:us
{"annotations_creators": ["no-annotation"], "language_creators": ["other"], "language": [], "license": ["lgpl-3.0"], "multilinguality": [], "size_categories": ["1M<n<10M"], "task_categories": [], "task_ids": [], "pretty_name": "Sketch Data Model Dataset"}
TAGS
#annotations_creators-no-annotation #language_creators-other #size_categories-1M<n<10M #license-lgpl-3.0 #region-us 

Dataset Card for Sketch Data Model Dataset
==========================================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information


Dataset Description
-------------------


* Homepage: URL
* Repository: URL
* Paper:
* Leaderboard:
* Point of Contact:


### Dataset Summary


This dataset contains over 6M CAD 2D sketches extracted from Onshape. Sketches are stored as python objects in the custom SAM format.
SAM leverages the Sketchgraphs dataset for industrial needs and allows for easier transfer learning on other CAD softwares.


### Supported Tasks and Leaderboards


Tasks: Automatic Sketch Generation, Auto Constraint


Dataset Structure
-----------------


### Data Instances


The presented npy files contain python pickled objects and require the flat\_array module of Sketchgraphs to be loaded. The normalization\_output\_merged.npy file contains sketch sequences represented as a list of SAM Primitives and Constraints. The sg\_merged\_final\_\*.npy files contain encoded constraint graphs of the sketches represented as a dictionnary of arrays.


### Data Fields


### Data Splits


Train: 6M, Val: 50k, Test: 50k


Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information



### Dataset Summary


This dataset contains over 6M CAD 2D sketches extracted from Onshape. Sketches are stored as python objects in the custom SAM format.
SAM leverages the Sketchgraphs dataset for industrial needs and allows for easier transfer learning on other CAD softwares. ### Supported Tasks and Leaderboards


Tasks: Automatic Sketch Generation, Auto Constraint


Dataset Structure
----------------- ### Data Instances


The presented npy files contain python pickled objects and require the flat\_array module of Sketchgraphs to be loaded. The normalization\_output\_merged.npy file contains sketch sequences represented as a list of SAM Primitives and Constraints. The sg\_merged\_final\_\*.npy files contain encoded constraint graphs of the sketches represented as a dictionnary of arrays. ### Data Fields ### Data Splits


Train: 6M, Val: 50k, Test: 50k


Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information
TAGS
#annotations_creators-no-annotation #language_creators-other #size_categories-1M<n<10M #license-lgpl-3.0 #region-us 
 ### Dataset Summary


This dataset contains over 6M CAD 2D sketches extracted from Onshape. Sketches are stored as python objects in the custom SAM format.
SAM leverages the Sketchgraphs dataset for industrial needs and allows for easier transfer learning on other CAD softwares. ### Supported Tasks and Leaderboards


Tasks: Automatic Sketch Generation, Auto Constraint


Dataset Structure
----------------- ### Data Instances


The presented npy files contain python pickled objects and require the flat\_array module of Sketchgraphs to be loaded. The normalization\_output\_merged.npy file contains sketch sequences represented as a list of SAM Primitives and Constraints. The sg\_merged\_final\_\*.npy files contain encoded constraint graphs of the sketches represented as a dictionnary of arrays. ### Data Fields ### Data Splits


Train: 6M, Val: 50k, Test: 50k


Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information