Task Creation

To create a task, the toolkit requires to upload the infomation into a server that Scale has access to. (Usually this implies a valid S3 credentials, an S3 bucket). The uploaded files are a list of json files that holds data such as device position, images, camera positions, points, and any other data that’s relevant.

And a valid Scale API key to create the task.

S3

The lidar toolkit uses boto3, which will use the aws credentials stored in ~/.aws/credentials.json (this is similar aws-cli in terminal).

The method scene.s3_upload(bucket, path) uses boto3 to upload all the attachments and images of the scene into the specified bucket and path.

scene.s3_upload('scaleapi-sales-test', path='test/lidar-toolkit')

Scale File Upload

As an alternative you can use the new feature Scale File upload, more info here. In order to use Scale File Upload replace the following line:

scene.s3_upload(bucket, path)

with

attachments = scene.scale_file_upload('project_name')

Replace project_name with which project these files should be associated with.

The method scale_file_upload returns a list of URL of the scene’s frame. This is what should be included in your lidar task’s attachments field (as part of the payload).

with open('template.json') as json_file:
    TEMPLATE = json.load(json_file)

if __name__ == '__main__':
    scene = create_scene(
            'data/',
            frames=range(1,6)
            )

    # Debugging methods
    #  scene.get_frame(index=1).add_debug_lines()
    #  scene.preview()

    # Upload data to S3 bucket
    attachments = scene.scale_file_upload('test_project')
    TEMPLATE['attachments'] = attachments
    # Create tasks/ Scale API request
    scene.create_task(TEMPLATE).publish()

Scale Api Key

Before you can create a task on Scale’s platform, you need to define an environment variable called SCALE_API_KEY . You can do this by entering export SCALE_API_KEY=live_xxxx in your terminal.

The following method is used to to create a task:

scene.create_task().publish()

With everything finally in place, you should be able to debug your data, upload it to S3 or your cloud provider of choice, and create tasks in Scale’s platform!

Template

Scene.create_task() supports a json template, which is used to generate the payload containing the task parameters from Scale’s documentation (labels, project name, instructions, etc).

# Code example of how to load a template.json file and use it
with open('template.json') as json_file:
    TEMPLATE = json.load(json_file)
scene.create_task(template).publish()

Example of template.json:

{
  "attachment_  type": "json",
  "callback_ur  l": "http://example.com/callback",
  "project": " default_project",
  "instruction": "Please label the objects on the scene",
  "labels": [
    "car",
    "truck",
    "bus",
    "bicycle",
    "motorbike",
    "towed_object",
    "person"
  ],
  "max_distance_meters": 20,
  "meters_per_unit": 1
}

Create the Task

Comment out the lidar debug lines, uncomment the s3 and task creation lines.

Add your task template and run the script to create your task!

with open('template.json') as json_file:
    TEMPLATE = json.load(json_file)

if __name__ == '__main__':
    scene = create_scene(
            'data/',
            frames=range(1,6)
            )

    # Debugging methods
    #  scene.get_frame(index=1).add_debug_lines()
    #  scene.preview()

    # Upload data to S3 bucket
    scene.s3_upload(S3_BUCKET, path='test-scale')
    # Create tasks/ Scale API request
    scene.create_task(TEMPLATE).publish()