Prediction

Use task_type predict with current and previous scene context to predict likely future spatial states.

What it answers

Given where things were and are, where do they go next?

task_type: predict

What to send

input.point_cloud_sceneobject

Current scene state.

input.previous_point_cloud_sceneobject

Prior state. Without it there is no motion history to extrapolate.

Every field on the request schema is still accepted; these are the ones this task depends on.

What comes back

spatial_prediction.objects

Projected positions per tracked object.

spatial_prediction.confidence

Per-object confidence.

spatial_prediction.horizon

How far ahead the estimate reaches.

Example

Terminal

$ curl https://fourechelon.com/api/v1/responses \
    -H "Authorization: Bearer $FOUR_ECHELON_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
$     "model": "rowe-1.0",
$     "input": {
$       "task_type": "predict",
$       "previous_point_cloud_scene": { "point_clouds": [] },
$       "point_cloud_scene": { "point_clouds": [] }
$     }
$   }'

Worth knowing

Prediction needs two states. Sending only the current scene returns present-state reasoning, not a forecast.