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Batch Open-vocabulary Detection with Grounding Models #18

Description

@NetZissou

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Add a batch pipeline that takes

  • (a) an image corpus (folder or Parquet of binary images/URIs) and,
  • (b) one or more text labels, and returns detection boxes (with scores + optional masks) for each image/label using an open-vocabulary grounding model such as OWLv2

Objective

  • Support open-vocabulary text prompts

    • Single label
    • Multiple labels
  • Run efficiently on GPU(s) with batch inference

  • Emit results in interoperable formats with stable schema

Example

One Label Detection

- RGB Image
- Text Label: ["Fish"]
Image

Multi-labels Detection

- RGB Image
- Text Label: ["coffee mug", "plate", "spoon"]
Image

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