Gureumi/VRChat_Avatar_Detection

VRChat Avatar Detection

Model Description

This model is the YOLO object detection model used in programs that detect avatars and name tags in a VRChat environment to determine which avatar belongs to whom.

Dataset Information

• Train Images: 13,565
• Validation Images: 1,507
• Image Size: 1920x1080 ~ 15360x8360
• Data Source: Photos captured using the in-game camera over 7 years of VRChat gameplay, along with frame data extracted from 1,707 hours of recorded video footage.

Data Filtering & Preprocessing

• Included: Humanoid 3D avatars only.
• Excluded: Non-humanoid avatars, Fallback avatars, default robot avatar, and Impostor avatars.

Training Configuration

• Task: Object Detection
• Base Framework: Ultralytics YOLO26
• Input Resolution(imgsz): 1920

Usage

from ultralytics import YOLO

model = YOLO("yolo26m_vrchat_avatar.pt")
results = model.predict(source="vrchat_screenshot.png", imgsz=1920, conf=0.5)
results[0].show()

Performance

Metric	Score (%)
mAP@50	96.30
mAP@50-95	81.30
Precision	96.50
Recall	92.80
F1 Score	94.61
Parameters	20.35M
FLOPs	68.1B
Inference	4.7ms (NVIDIA H100) 12.2ms (RTX 5070Ti)

Per-Class Performance

Class	Images	Instances	Precision (%)	Recall (%)	mAP@50 (%)	mAP@50-95 (%)
avatar	1455	2777	95.90	90.80	95.80	79.80
nametag	121	268	97.10	94.80	96.80	82.80
all	1507	3045	96.50	92.80	96.30	81.30

Known Limitations

Performance may degrade in:

• Severe motion blur or particle & SFX hell environments
• Humanoid furry (I don't have many furry humanoid photos)
• Types of humanoid avatars I have never seen