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YOLOE: Universal Object Detection in X-AnyLabeling

Overview

YOLOE (You Only Look Once, Extended) brings state-of-the-art "anything" detection capabilities to X-AnyLabeling. Based on the research paper YOLOE, this model enables real-time detection and segmentation of any object you can describe or indicate visually, eliminating traditional category constraints.

Installation

Prerequisites

Create a dedicated conda environment for YOLOE:

conda create -n yoloe python=3.10 -y
conda activate yoloe

YOLOE Setup

Clone and install the YOLOE repository:

git clone https://github.com/THU-MIG/yoloe.git
cd yoloe
pip install -r requirements.txt

Note: For complete YOLOE documentation, visit the official repository.

X-AnyLabeling Integration

Install X-AnyLabeling in the same environment:

cd ..
git clone https://github.com/CVHub520/X-AnyLabeling.git
cd X-AnyLabeling
pip install -r requirements.txt

Note: See our installation guide (English | Chinese) for detailed instructions.

Launch the application:

python anylabeling/app.py

Detection Modes

YOLOE.mp4

YOLOE supports three distinct detection modes, each optimized for different use cases:

Text Prompting

Specify target objects using natural language descriptions.

Usage:

  1. Enter object names in the text field (e.g., person, car, bicycle)
  2. Separate multiple classes with periods or commas: person.car.bicycle or dog,cat,tree
  3. Click Send to initiate detection

This mode leverages YOLOE's text understanding capabilities to identify objects based on semantic descriptions.

Visual Prompting

Guide detection by marking examples directly on the image.

Usage:

  1. Click +Rect to activate drawing mode
  2. Draw bounding boxes around target objects or regions of interest
  3. Add multiple prompts for different object instances
  4. Click Send to process visual cues or use Clear to remove all visual prompts

Visual prompts help YOLOE understand object characteristics through spatial context and appearance.

Prompt-Free Detection

Detect objects from a predefined class vocabulary without explicit prompting.

Activation: Click Send with no text input and no visual prompts.

Class Configuration: Customize the detection vocabulary in your YOLOE configuration file (e.g., yoloe_v8l.yaml):

Option 1: List Format

type: yoloe
...
classes:
  - person
  - vehicle
  - animal
  - furniture

Option 2: Dictionary Format

type: yoloe
...
classes:
  0: person
  1: vehicle
  2: animal
  3: furniture

Option 3: External File

type: yoloe
...
classes: /path/to/classes.txt

Where classes.txt contains one class per line:

person
vehicle
animal
furniture

Default Behavior: When no classes field is specified, X-AnyLabeling uses a comprehensive vocabulary from here.

Batch Processing

Process multiple images efficiently using consistent detection parameters.

Activation: Press Ctrl+M (Windows/Linux) or Cmd+M (macOS)

Supported Modes:

  • Text Prompting: Enter text prompts before starting batch processing to apply them across all images
  • Prompt-Free: Leave text field empty to use configured class vocabulary for all images

Note: Visual prompting is not available in batch mode due to its interactive nature.