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 |
|---|---|---|---|
| name | str | A short, descriptive name for the detector. | [optional] |
| 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] |