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Visual models

legopolitics separates specialized visual models from general vision-language models.

  • Florence-2: captioning, region descriptions, grounding, detection-style tasks, and OCR.
  • BLIP / BLIP-2: captioning and visual question answering.
  • CLIP: image-text similarity, zero-shot labels, and agreement analysis.
  • DINOv2: visual embeddings, clustering, representative crops, and re-identification support.
  • Hugging Face image-text-to-text VLMs: open-ended frame, crop, and sequence interpretation.

Multiple Hugging Face models can be configured under vision.models.huggingface_vlms. Their raw outputs and provenance remain separate so the ensemble layer can compare model agreement rather than overwriting predictions. See Hugging Face VLM Ensemble.