Groundlight Detectors provide answers to natural language questions about images. Each detector can answer a single question, and multiple detectors can be strung together for more complex logic. Detectors can be created through the create_detector method, or through the create_[MODE]_detector methods for pro tier users
Name | Type | Description | Notes |
---|---|---|---|
id | str | A unique ID for this object. | [readonly] |
type | bool, date, datetime, dict, float, int, list, str, none_type | The type of this object. | [readonly] |
created_at | datetime | When this detector was created. | [readonly] |
name | str | A short, descriptive name for the detector. | |
query | str | A question about the image. | [readonly] |
group_name | str | Which group should this detector be part of? | [readonly] |
metadata | {str: (bool, date, datetime, dict, float, int, list, str, none_type)}, none_type | Metadata about the detector. | [readonly] |
mode | bool, date, datetime, dict, float, int, list, str, none_type | [readonly] | |
mode_configuration | {str: (bool, date, datetime, dict, float, int, list, str, none_type)}, none_type | [readonly] | |
confidence_threshold | float | If the detector's prediction is below this confidence threshold, send the image query for human review. | [optional] if omitted the server will use the default value of 0.9 |
patience_time | float | How long Groundlight will attempt to generate a confident prediction | [optional] if omitted the server will use the default value of 30.0 |
status | bool, date, datetime, dict, float, int, list, str, none_type | [optional] | |
escalation_type | bool, date, datetime, dict, float, int, list, str, none_type | Category that define internal proccess for labeling image queries * `STANDARD` - STANDARD * `NO_HUMAN_LABELING` - NO_HUMAN_LABELING | [optional] |
any string name | bool, date, datetime, dict, float, int, list, str, none_type | any string name can be used but the value must be the correct type | [optional] |