Localises the noun phrases of a caption in an image: it runs Florence-2 phrase grounding over an Image and a String, emitting either bare [Rectangle<Double>] boxes or labelled `[{bounds, label}]` regions depending on how the output is wired.
Typical backends
Caption a frame, then ground the generated caption's phrases and crop the regions.
Ground an operator-supplied phrase in a fetched image and draw the regions.
Caveats
- I/O contractThe phrase is a per-frame
String; an empty phrase or an empty Image yields an empty result rather than an error, so silent or unframed ticks produce zero regions. - AccuracyGrounding only finds noun phrases that the supplied caption mentions, so a phrase describing something absent from the frame returns nothing; pair it with a captioner to ground generated text or feed an operator phrase directly.
- I/O contractLabels are free-form phrase fragments with no fixed class-id space, which is why the labelled arm emits `{bounds, label}` records rather than enumerated boxes; the geometry-only arm drops the labels.
- FallbackInference failures on a single frame are caught and logged, returning an empty result for that frame instead of crashing, so transient errors degrade to gaps rather than a halt.
- LatencyThis is a beam-searched sequence-to-sequence vision model; CPU execution is impractical for live video, and the device binds once at startup so it cannot be switched at runtime.