Stop retraining YOLO: a developer’s guide to zero-shot object detection with generative VLMs

The guide shows how generative vision-language models can detect objects from natural-language prompts, reducing the need to retrain classic detectors like YOLO or Faster R-CNN.

It focuses on zero-shot object detection for industrial inspection use cases such as factories, warehouses, and construction sites, where object classes change often.

The article compares self-hosted open-source deployment with managed API usage, including tradeoffs in compute, latency, privacy, and operational complexity.

It also highlights practical tooling for structured bounding-box outputs, with models and libraries such as LLaVA, GPT-4o, Hugging Face Transformers, and Pydantic.