Supervisely

Overview

Easily import your pointclouds with annotations in the Supervisely format. The Supervisely json-based annotation format supports cuboid_3d shape figures. It is a universal format that supports various types of annotations and is used in the Supervisely platform.

All information about the Supervisely JSON format can be found here

Format description

Supported point cloud format: .pcd With annotations: yes Supported annotation format: .json. Data structure: Information is provided below.

Input files structure

Example data: download ⬇️.

Both directory and archive are supported.

Recommended directory structure:

📦pointcloud_project (folder or .tar/.zip archive)
├──📄key_id_map.json (optional)
├──📄meta.json
├──📂dataset1
│ ├──📂pointcloud
│ │ ├──📄scene_1.pcd
│ │ ├──📄scene_2.pcd
│ │ └──📄...
│ ├──📂related_images
│ │   ├──📂scene_1_pcd
│ │   │ ├──🏞️scene_1_cam0.png
│ │   │ ├──📄scene_1_cam0.png.json
│ │   │ ├──🏞️scene_1_cam1.png
│ │   │ ├──📄scene_1_cam1.png.json
│ │   │ └──📄...
│ │   ├──📂scene_2_pcd
│ │   │ ├──🏞️scene_2_cam0.png
│ │   │ ├──📄scene_2_cam0.png.json
│ │   │ ├──🏞️scene_2_cam1.png
│ │   │ ├──📄scene_2_cam1.png.json
│ │   │ └──📄...
│ │   └──📂...
│ └──📂ann
│     ├──📄scene_1.pcd.json
│     ├──📄scene_2.pcd.json
│     └──📄...
└──📂dataset...

Every .pcd file in a sequence has to be stored inside a pointcloud folder of datasets.

Key	Value
x	The x coordinate of the point.
y	The y coordinate of the point.
z	The z coordinate of the point.
r	The red color channel component. An 8-bit value (0-255).
g	The green color channel component. An 8-bit value (0-255)
b	The blue color channel component. An 8-bit value (0-255)

All the positional coordinates (x, y, z) are in meters. Supervisely supports all PCD encoding: ASCII, binary, binary_compressed.

The PCD file format description can be found here

related_images optional folder, contains photo-context data: - Frame folder, each named according to pointcloud (/related_images/scene_1_pcd/), which contains: - image files (.png \ .jpg) - photo context image annotation file (.json) - json files, named according to image name (1.png -> 1.png.json). Read more in the "Photo context image annotation file" section below.

Format of Annotations

Point cloud Annotations refer to each point cloud and contains information about labels on the point clouds in the datasets.

A dataset has a list of objects that can be shared between some point clouds.

The list of objects is defined for the entire dataset, even if the object's figure occurs in only one point cloud.

Figures represents individual labels, attached to one single frame and its object.

{
  "description": "",
  "key": "e9f0a3ae21be41d08eec166d454562be",
  "tags": [],
  "objects": [
    {
      "key": "ecb975d70735486b90fe4fdd2be77e3b",
      "classTitle": "Car",
      "tags": [],
      "labelerLogin": "admin",
      "updatedAt": "2022-05-04T00:32:30.872Z",
      "createdAt": "2022-05-04T00:32:30.872Z"
    }
  ],
  "figures": [
    {
      "key": "abbaec8785c1468585f6210c62bb2374",
      "objectKey": "ecb975d70735486b90fe4fdd2be77e3b",
      "geometryType": "cuboid_3d",
      "geometry": {
        "position": {
          "x": 58.756710052490234,
          "y": 4.623323917388916,
          "z": -0.4174150526523591
        },
        "rotation": {
          "x": 0,
          "y": 0,
          "z": -1.77
        },
        "dimensions": {
          "x": 1.59,
          "y": 4.28,
          "z": 1.45
        }
      },
      "labelerLogin": "admin",
      "updatedAt": "2022-05-04T00:32:37.432Z",
      "createdAt": "2022-05-04T00:32:37.432Z"
    }
  ]
}

Optional fields and loading These fields are optional and are not needed when loading the project. The server can automatically fill in these fields while project is loading.

• id - unique identifier of the current object

• classId - unique class identifier of the current object

• labelerLogin - string - the name of user who created the current figure

• createdAt - string - date and time of figure creation

• updatedAt - string - date and time of the last figure update

Main idea of key fields and id you can see below in "Key id map" file section.

Fields definitions:

• description - string - (optional) - this field is used to store the text to assign to the sequence.

• key - string, unique key for a given sequence (used in key_id_map.json to get the sequence ID)

• tags - list of strings that will be interpreted as point cloud tags

• objects - list of objects that may be present on the dataset

• geometryType - "cuboid_3d" or other 3D geometry - class shape

Fields definitions for objects field:

• key - string - unique key for a given object (used in key_id_map.json)

• classTitle - string - the title of a class. It's used to identify the class shape from the meta.json file

• tags - list of strings that will be interpreted as object tags (can be empty)

Fields description for figures field:

• key - string - unique key for a given figure (used in key_id_map.json)

• objectKey - string - unique key to link figure to object (used in key_id_map.json)

• geometryType - "cuboid_3d" or other 3D geometry -class shape

• geometry - geometry of the object

Description for geometry field (cuboid_3d):

• position 3D vector of box center coordinates:

  • x - forward in the direction of the object

  • y - left

  • z - up

• dimensions is a 3D vector that scales a cuboid from its local center along x, y, z:

  • x - width

  • y - length

  • z - height

• rotation is a 3D Vector that rotates a cuboid along an axis in world space:

  • x - pitch

  • y - roll

  • z - yaw (direction)

Rotation values bound inside [-pi ; pi] When yaw = 0 box direction will be strict +y

Read more about the key_id_map.json file and photo context annotations in the documentation here.

Photo context image annotation file

    {
        "name": "host-a005_cam4_1231201437716091006.jpeg"
        "entityId": 2359620,
        "meta": {
            "deviceId": "CAM_BACK_LEFT",
            "timestamp": "2019-01-11T03:23:57.802Z",
            "sensorsData": {
                "extrinsicMatrix": [
                    -0.8448329028461443,
                    -0.5350302199120708,
                    0.00017334762588639086,
                    -0.012363736761232369,
                    -0.0035124448582330757,
                    0.005222293412494302,
                    -0.9999801949951969,
                    -0.16621728572112304,
                    0.5350187183638307,
                    -0.8448167798004226,
                    -0.006291229448121315,
                    -0.3527897896721229
                ],
                "intrinsicMatrix": [
                    882.42699274,
                    0,
                    602.047851885,
                    0,
                    882.42699274,
                    527.99972239,
                    0,
                    0,
                    1
                ]
            }
        }
    }

Fields description:

• name - string - Name of image file

• Id - (OPTIONAL) - integer >= 1 ID of the photo in the system. It is not required when upload and is filled in automatically when the project is loaded.

• entityId (OPTIONAL) - integer >= 1 ID of the Point Cloud in the system, that photo attached to. Doesn't required while uploading.

• deviceId - string- Device ID or name.

• timestamp - string - Time when the frame occurred in ISO 8601 format

• sensorsData - Sensors data such as Pinhole camera model parameters. See wiki: Pinhole camera model and OpenCV docs for 3D reconstruction.

  • intrinsicMatrix - Array of number - 3x3 flatten matrix (dropped last zeros column) of intrinsic parameters in row-major order, also called camera matrix. It's used to denote camera calibration parameters. See Intrinsic parameters.

  • extrinsicMatrix - Array of number - 4x3 flatten matrix (dropped last zeros column) of extrinsic parameters in row-major order, also called joint rotation-translation matrix. It's used to denote the coordinate system transformations from 3D world coordinates to 3D camera coordinates. See Extrinsic_parameters.

Useful links

• Supervisely Annotation Format

• Supervisely Pointcloud Annotation

• [CLI Tool Beta] Upload projects in Supervisely format

• [SDK CLI] Upload projects in Supervisely format

• Import Point Cloud Project app.

• Export pointclouds project in Supervisely format app.

• Demo pointcloud project with labels