How to Detect Objects with YOLO-World

YOLO-World, developed by Tencent's AI Lab, is an innovative real-time, zero-shot object detection model that allows users to identify objects in images through text prompts without prior training or fine-tuning. This model introduces a novel "prompt then detect" paradigm, enhancing speed by eliminating the need for just-in-time text encoding, unlike other zero-shot models such as Grounding DINO. YOLO-World's small version achieves up to 74.1 FPS on a V100 GPU, and it can be deployed on personal hardware using the Roboflow Inference Python package. The guide details the process of setting up and running YOLO-World for object detection, including installing dependencies, importing data, running the model, and visualizing results using the Supervision Python package. Additionally, it addresses challenges such as low confidence levels and overlapping bounding boxes, offering solutions like adjusting confidence thresholds and applying Non-Maximum Suppression (NMS) for improved outputs.