hjLabs AI Playground
Starting the on-device runtime…
OWL-ViT locates objects from a text prompt rather than a fixed label set, so you can ask for "a red safety helmet", "cracked tile" or "barcode" and get boxes back without collecting a single training image. That makes it the fastest way to test whether a detection idea is viable at all before anyone annotates a dataset. Accuracy trails a fine-tuned detector, but the iteration loop is seconds instead of weeks — and it all runs on your GPU.
zero shot object detectionowl-vit demotext prompt object detectionopen vocabulary detectionfind objects by descriptionno training detectiongrounding detection online
Short noun phrases work best — "a person wearing a hard hat" beats a full sentence. Give several candidate phrases at once and compare their scores.
Whenever the thing you are looking for is not one of the 80 COCO classes, or when you are still exploring what to look for. Once the class list is fixed and you need accuracy, fine-tune a real detector.