翻译状态： 此任务示例目前仅提供英文版本。

LocateAnything: Open-Vocabulary Grounding in X-AnyLabeling

Overview

LocateAnything is a vision-language grounding model that returns boxes and points using normalized coordinates. X-AnyLabeling integrates it through X-AnyLabeling-Server, so inference runs in a dedicated server environment and the client receives standard annotation shapes.

LocateAnything supports several remote tasks:

Task	Input	Output
Detection	Object categories such as person, car, bicycle	Rectangle boxes
Grounding	A natural-language phrase such as people wearing red shirts	Rectangle boxes
Pointing	A phrase such as the traffic light	Point shapes
Text Detection	No text prompt	Text boxes with recognized text stored in shape descriptions

Visual Demo

Dense Object Detection LocateAnything performs diverse localization tasks under a unified VLM — document understanding, GUI grounding, dense object detection, and OCR.

Fast Decoding Speed Parallel Box Decoding (PBD) vs. Quantized Coordinate Decoding — PBD predicts each bounding box atomically in a single forward pass for substantially faster throughput.

Server-side

Installation

Create or reuse a dedicated environment for LocateAnything. Do not install it through the server [all] extra, because LocateAnything requires transformers>=4.50,<5, while some other server models require Transformers 5.x.

conda activate locateanything
cd /path/to/X-AnyLabeling-Server

pip install --upgrade uv
uv pip install -e .[locateanything]

Make sure PyTorch is installed with the CUDA version that matches your machine. The server extra installs the X-AnyLabeling-Server core dependencies plus:

transformers>=4.50,<5
peft

Enable the Model

In X-AnyLabeling-Server, enable LocateAnything in configs/models.yaml:

enabled_models:
  - locateanything

The model config is located at:

configs/auto_labeling/locateanything.yaml

Common parameters:

Parameter	Default	Description
model_path	nvidia/LocateAnything-3B	Hugging Face model id or local model path
device	cuda	PyTorch device, for example cuda, cuda:0, cuda:1, or cpu
dtype	bfloat16	Inference dtype
max_image_size	1024	Resize the long edge before inference
max_new_tokens	512	Maximum generation length
generation_mode	hybrid	Supported values: fast, slow, hybrid
temperature	0.7	Sampling temperature used by the original worker default
verbose	false	Print generation statistics in server logs

Start the server:

uvicorn app.main:app --host 0.0.0.0 --port 8000

Usage

Launch X-AnyLabeling, press Ctrl+A or click the AI button in the left menu bar to open the auto-labeling panel. In the model dropdown list, select Remote-Server, then choose LocateAnything.

Detection

Use this mode when you want to find one or more object categories.

1. Select Detection in the task dropdown.
2. Enter object names in the text field, for example person, car, or bicycle.
3. Separate multiple categories with periods: person.car.bicycle.
4. Click Send to run inference.

Note

LocateAnything may produce weaker results when detecting multiple target categories in one prompt. For practical annotation work, single-target detection is recommended when accuracy matters.

The default max_image_size is set to 1024 as a conservative value for GPUs with limited memory, such as an RTX 3060 with about 11 GB VRAM. Increasing the inference resolution can improve detail, but when the visual tokens approach the GPU memory limit, prefill latency can increase sharply. In local tests, prefill time increased from roughly 1-2 seconds to about 100+ seconds at a much larger resolution. Tune max_image_size according to your GPU memory.

If you request many targets or expect many output boxes, increase max_new_tokens accordingly.

Grounding

Use this mode when the target is better described as a phrase.

1. Select Grounding in the task dropdown.
2. Enter a phrase such as people wearing red shirts.
3. Click Send to run inference.

Pointing

Use this mode when you want point annotations instead of boxes.

1. Select Pointing in the task dropdown.
2. Enter a phrase such as the search button or the traffic light.
3. Click Send to run inference.

Text Detection

Use this mode to detect scene text.

1. Select Text Detection in the task dropdown.
2. Click Run.

Text detection returns rectangle shapes with label object. Recognized text is stored in each shape's description field.

Notes

• The model outputs coordinates as integers in [0, 1000]; the server maps them back to the original image size.
• Reducing max_image_size can greatly reduce prefill latency and GPU memory usage.
• Keep LocateAnything in a separate server environment from models that require Transformers 5.x.