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license: agpl-3.0
metrics:
- map50
- map50-95
- precision
- recall
- f1
base_model:
- Ultralytics/YOLO26
pipeline_tag: object-detection
tags:
- yolo
- vision
- object-detection
- vrchat
- vrchat-avatar
- vrchat-nametag
- avatar-detection
model-index:
- name: VRChat_Avatar_Detection (YOLO26m)
results:
- task:
type: object-detection
name: Object Detection
metrics:
- name: mAP@50
type: map50
value: 96.30
- name: mAP@50-95
type: map50-95
value: 81.30
- name: Precision
type: precision
value: 96.50
- name: Recall
type: recall
value: 92.80
- name: F1-Score
type: f1
value: 94.61
---
# VRChat Avatar Detection
<p style="display: grid;grid-template-columns: auto auto">
<a href="https://huggingface.co/Gureumi/VRChat_Avatar_Detection/blob/main/result_1920.jpg">
<img src="result_1920.jpg" alt="1920x1080 image">
</a>
<a href="https://huggingface.co/Gureumi/VRChat_Avatar_Detection/blob/main/result_7680.jpg">
<img src="result_7680.jpg" alt="7680x4320 image">
</a>
<a href="https://huggingface.co/Gureumi/VRChat_Avatar_Detection/blob/main/result_avatar&nametag.png">
<img src="result_avatar&nametag.png" alt="avatar&nametag detection image">
</a>
<a href="https://huggingface.co/Gureumi/VRChat_Avatar_Detection/blob/main/result_avatar&nametag_2.png">
<img src="result_avatar&nametag_2.png" alt="avatar&nametag detection image">
</a>
</p>
## 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
```python
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)<br>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 |