Descriptions:
NVIDIA’s LocateAnything is a 3-billion-parameter vision-language model that goes beyond standard image classification to precisely localize objects, text, and UI elements within images and video. Trained on 12 million images, the model functions as a generalist spatial-reasoning engine suited for robotics, autonomous driving, automated data labeling, and GUI automation.
In this hands-on walkthrough, Fahd Mirza installs the model locally on Ubuntu using an NVIDIA RTX A6000 GPU with 48GB of VRAM, running it through a Gradio interface built on top of the official HuggingFace release. The model weighs under 5GB across two shards and uses just over 8GB of VRAM during inference — a notably light footprint. Mirza walks through all five supported task modes: object detection (bounding boxes over category instances), grounding (natural-language-driven localization, e.g., “the red car”), OCR (text detection and labeling), GUI element identification (finding named interface elements on screen), and pointing (predicting a precise XY coordinate for a target).
The GUI and pointing modes are highlighted as a practical foundation for building computer-use agents — LocateAnything can identify an exact pixel location for any on-screen element, which downstream tooling can then act on. Video inference is also demonstrated, though GPU memory constraints limit throughput. Developers exploring visual grounding, document parsing, or agent-driven browser automation will find this model’s combination of natural-language input and spatial precision worth evaluating.
📺 Source: Fahd Mirza · Published June 01, 2026
🏷️ Format: Tutorial Demo
