Documentation
  • Introduction
  • Tutorials
    • Getting started
    • Python SDK quickstart
    • Model-assisted labeling
  • How to annotate
    • Label images
      • View and navigate in the image interfaces
      • Image interface settings
      • Image segmentation interface
      • Image vector interface
    • Label 3D point clouds
      • View and navigate in the 3D interface
      • Upload, view, and overlay images
      • 3D interface settings
      • 3D point cloud cuboid interface
      • 3D point cloud vector interface
      • 3D point cloud segmentation interface
      • Merged point cloud view (for static objects)
      • Batch mode (for dynamic objects)
      • Smart cuboid propagation
      • 3D to 2D Projection
      • Tips for labeling cuboid sequences
    • Label sequences of data
      • Use track IDs in sequences
      • Use keyframe interpolation
    • Annotate object links (beta)
    • Customize hotkeys
  • How to manage
    • Add collaborators to a dataset
    • Create an organization
    • Configure the label editor
    • Customize label queue
    • Search within a dataset
    • Clone a dataset
    • Work with issues
    • Bulk change label status
    • Manage QA processes
  • How to integrate
    • Import data
      • Cloud integrations
    • Export data
      • Structure of the release file
      • Exporting image annotations to different formats
    • Integrations
      • Hugging Face
      • W&B
      • Databricks
      • SceneBox
    • Create an API key
    • Upload model predictions
    • Set up webhooks
  • Background
    • Main concepts
    • Sequences
    • Label queue mechanics
    • Labeling metrics
    • 3D Tiles
    • Security
  • Reference
    • Python SDK
    • Task types
    • Sample formats
      • Supported file formats
    • Label formats
    • Categories and attributes
    • API
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On this page
  • Image
  • 3D point cloud
  • PCD (Point Cloud Data)
  • Binary xyzi(r) (KITTI/nuScenes)
  • PLY (Stanford Triangle Format)
  • LAS
  • Gaussian Splat
  • .splat

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  1. Reference
  2. Sample formats

Supported file formats

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Last updated 10 months ago

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Image

Following image file formats are supported: jpeg, png, bmp.

3D point cloud

PCD (Point Cloud Data)

of the PCD format is supported. PCD files can either be ASCII-encoded or binary files. The PCD files should contain at least x, y, and z coordinate fields. Optionally, you can supply an intensity or an RGB field. These fields are used for setting the color of the points. Intensity coloring can be enabled or disabled in the viewer.

Any other fields will be ignored.

Field name
Size (#bytes)
Type
Required

x

4

float

y

4

float

z

4

float

intensity

4

float

rgb

4

float

Please make sure that you supply the values as 32-bit (=4 byte) floats.

Keep in mind that 32-bit floats have limited precision. In fact, only 24 bits can be used to represent the number itself (the significand, excluding the sign bit), or about 7.22 decimal digits. If you want to keep two decimal places, this only leaves 5.22 decimal digits, so the numbers shouldn't be larger than 10^5.22 = 165958.

To avoid rounding problems, it is best practice to subtract the ego position of the first frame from all other ego positions. This way, the first ego position is set to (0, 0, 0) and the subsequent ego positions are relative to (0, 0, 0) . In your export script, you can add the ego position of the first frame back to the object positions.

Binary xyzi(r) (KITTI/nuScenes)

Field name
Size (#bytes)
Type
Required

x

4

float

y

4

float

z

4

float

intensity

4

float

ring index

4

float

PLY (Stanford Triangle Format)

The PLY file format can be used for point clouds by encoding the points as vertices. The PLY header should thus contain a vertex element containing x, y, and z properties and optionally also color or intensity properties. Both binary and ASCII PLY files are supported.

PLY Gaussian Splats are not supported

Property name
Type
Required

x

float32

y

float32

z

float32

red

uchar [0, 255]

green

uchar [0, 255]

blue

uchar [0, 255]

intensity

float32

LAS

  • LAS support is limited to 3D cuboid and 3D vector task types. It is not supported for 3D point cloud segmentation.

  • The LAS file format is currently only recommended for huge point clouds (e.g. merged maps) that cannot be tiled otherwise.

Point clouds can optionally include RGB fields, or an intensity field. If both are defined, the intensity will be discarded.

  • For point clouds with RGB colors, make sure to set the point format field to 2.

  • For point clouds with intensity values, make sure to set the point format field to 0.

Keep in mind to set the LAS scale/resolution small enough (e.g. 1e-6) to avoid discretization errors.

Property name
Type
Required

X

float32

Y

float32

Z

float32

Red

uint8 [0-255]

Green

uint8 [0-255]

Blue

uint8 [0-255]

Intensity

uint8 [0-255]

Gaussian Splat

.splat

Segments.ai supports the binary point cloud formats used by the and datasets. These formats do not contain a header and have a fixed number of fields. When uploading a sample with point clouds in one of these formats, use binary-xyzi (alias kitti) or binary-xyzir (alias nuscenes) for the type field.

Unlike other file formats, the uploaded files can only be viewed after the is completed.

of the LAS file format is supported. Only uncompressed LAS files are currently supported.

Gaussian splats can only be uploaded as .splat files at the moment. PLY splat files are not supported. If you want to convert your splat file from PLY to .splat, you can either use , an online splat editor, or the open-source library.

Version 0.7
KITTI
nuScenes
tiling process
Version 1.4
SuperSplat
point-cloud-tool