Supported Datasets¶

Overview¶

SketchKit provides a variety of sketch-based datasets for research on sketch recognition, retrieval, and generation, including most of current popular datasets.

All datasets share a unified interface, so you can load them, search sketches by metadata, or convert sketches into the standard Sketch format easily.

Metadata¶

Each dataset object provides an attribute items_metadata, pandas.DataFrame, which contains useful information for searching and filtering sketches.

items_metadata is your main tool to search, filter, and batch load sketches efficiently.

id: unique identifier of each sketch.

sub_id: optional sub-identifier used when one original item contains multiple sketches or derived samples.

category: sketch category (e.g., “cat”, “dog”, “chair”).

split: dataset split (e.g., “train”, “test”, “val”), available in some datasets.

…

Key concepts of dataset parameters¶

root: Datatype: str, Default: "~/.sketchkit/datasets"

Directory where the dataset is stored or downloaded.

If the dataset is not present locally, it will be automatically downloaded to this path.

root dictionary can be costumed, if not, it will store datasets in the default path.

Examples:
# Store the dataset in a temporary directory
dataset = ControlSketch(root=tmpdir)

# Store the dataset in a custom local directory
dataset = ControlSketch(root="./controlsketch")

load_all: Datatype: bool, Default: False

Whether to load all sketches in the dataset into memory at once.

False: Load metadata only, sketch can be loaded on demand via metadata.

True: Load the entire dataset into memory, having faster access but higher RAM usage.

Example:
dataset = ControlSketch(load_all=True)

cislab_source: Datatype: bool, Default: False

Whether to download the dataset from the CIS LAB mirror site or original download link.

False: Use default source (e.g., Github/official download link) to download dataset.

True: Apply CIS LAB mirror site to download dataset.

Example:
dataset = ControlSketch(cislab_source=True)

download: Datatype: bool, Default: True

Automatically download the dataset if it is missing locally.

True: As description.

False: Not recommended. You need to provide the dataset manually, otherwise an error is raised.

split: Datatype: str, Default: "train"

Select which split of the dataset to load. (e.g., “train”, “test”, “val”)

Example:
validation = dataset.items_metadata[dataset.items_metadata["split"] == "validation"]

category: Datatype: list[str], Default: None

Load only specific categories of sketches. (e.g., “cat”, “dog”, “chair”)

Example:
bears = dataset.items_metadata[dataset.items_metadata["category"] == "bear"]

Tip

load_all should be chosen based on dataset size and memory availability: use False for large datasets.
split and categories can be combined to load subset you need.
cislab_source is applicable to most mainstream dataset.

Loading a dataset¶

# Default load (metadata only)
dataset = ControlSketch()

# Load all data into memory at once
dataset = ControlSketch(load_all=True)

Searching sketches by metadata¶

# Search items using metadata
bears = dataset.items_metadata[
         (dataset.items_metadata["category"] == "bear")
         & (dataset.items_metadata["split"] == "validation")
     ]

# Load sketches based on metadata
bears_sketch = [dataset[row.id] for _, row in bears[:100].iterrows()]

Available Datasets¶

The following are the built-in sketch datasets currently available in SketchKit. Each dataset has its own manual page in this section so you can customize descriptions and examples.

Dataset Feature¶

The following table shows features of each built-in SketchKit dataset.

Vector representation (polyline or Bézier curve) used in the original datasets.

Dataset	Representation
`LineDrawer`	Polyline
`QuickDraw`	Polyline
`ControlSketch`	Bézier
`TUBerlin`	Bézier
`TracingVsFreehand`	Polyline
`OpenSketch`	Polyline
`SketchXPRIS`	Polyline
`Sketchy`	Bézier
`PhotoSketching`	Bézier
`GMUSketchCleanup`	Bézier
`FSCOCO`	Polyline
`DifferSketching`	Polyline
`CreativeSketch`	Polyline
`SketchIME`	Polyline

How to contribute a new dataset to SketchKit¶

You can integrate a new or customized dataset into SketchKit following the step-by-step document.