Models
Truebees detection is powered by a set of specialised machine learning models. Understanding which model produced a verdict helps you interpret results, tune your thresholds, and reason about edge cases.
Pipelines vs. models
A pipeline is a named detection configuration you reference in the API (e.g., pipeline=cantaloupe). Internally, a pipeline may invoke one or more models in sequence. The model name returned in the verdict identifies which specific model scored the submitted image.
For example, the cantaloupe pipeline runs both the Cantaloupe deepfake detector and the Azalea social-media classifier. Each model contributes its own score to the verdict.
See Verification API Deep Dive for how to specify a pipeline in a request, and Platform Concepts for how to interpret the score and status fields in a verdict.
Available models
| Model | Type | Brief description |
|---|---|---|
| Cantaloupe | Deepfake image detector | ResNet-50-based detector that scores the squared distance of image features from learned reference centres |
| Azalea | Social-media classifier | Stacking ensemble detector that classifies whether an image has been shared or processed through social-media platforms |
Model cards
Each model page provides a high-level technical explanation suitable for integration and debugging. Detailed model cards — covering training datasets, evaluation benchmarks, and specific weight versions — will be published as sub-pages under each model as they become available.