Anzhcs_YOLOs / README.md
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---
license: agpl-3.0
tags:
- pytorch
- YOLOv8
- art
- Ultralytics
base_model:
- Ultralytics/YOLOv8
library_name: ultralytics
pipeline_tag: object-detection
metrics:
- mAP50
- mAP50-95
---
# Description
YOLOs in this repo are trained with datasets that i have annotated myself, or with the help of my friends(They will be appropriately mentioned in those cases). YOLOs on open datasets will have their own pages.
#### Want to request a model?
Im open to commissions, hit me up in Discord - **anzhc**
(Also if you want to support me - https://ko-fi.com/anzhc)
> ## **Table of Contents**
> - [**Face segmentation**](#face-segmentation)
> - [*Universal*](#universal)
> - [*Real Face, gendered*](#real-face-gendered)
> - [**Eyes segmentation**](#eyes-segmentation)
> - [**Head+Hair segmentation**](#headhair-segmentation)
> - [**Breasts segmentation**](#breasts-segmentation)
P.S. All model names in tables have download links attached :3
## Available Models
### Face segmentation:
#### Universal:
Series of models aiming at detecting and segmenting face accurately. Trained on closed dataset i annotated myself.
| Model | Target | mAP 50 | mAP 50-95 |Classes |Dataset size|Training Resolution|
|----------------------------------------------------------------------------|-----------------------|--------------------------------|---------------------------|---------------|------------|-------------------|
| [Anzhc Face -seg.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20Face%20-seg.pt) | Face: illustration, real | LOST DATA | LOST DATA |2(male, female)|LOST DATA| 640|
| [Anzhc Face seg 640 v2 y8n.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20Face%20seg%20640%20v2%20y8n.pt) | Face: illustration, real | 0.872(box),0.872(mask) | 0.835(box),0.752(mask)|1(face) |~500| 640|
| [Anzhc Face seg 768 v2 y8n.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20Face%20seg%20768%20v2%20y8n.pt) | Face: illustration, real | 0.86(box),0.86(mask) | 0.81(box),0.726(mask) |1(face) |~500| 768|
| [Anzhc Face seg 768MS v2 y8n.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20Face%20seg%20768MS%20v2%20y8n.pt) | Face: illustration, real | 0.866(box),0.866(mask) | 0.816(box),0.72(mask) |1(face) |~500| 768|(Multi-scale)|
| [Anzhc Face seg 1024 v2 y8n.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20Face%20seg%201024%20v2%20y8n.pt) | Face: illustration, real | 0.872(box),0.872(mask) | 0.804(box),0.726(mask)|1(face) |~500| 1024|
Take those stats with a grain of salt, since im pretty sure i re-scrambled dataset partition after training those models ages ago.
Benchmark was performed in 640px.
Difference in v2 models are only in their target resolution, so their performance spread is marginal.
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/G1vywwrYQOPSK9t3MZTen.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/jMTKRWVk5y0HhrqqePdp-.png)
#### Real Face, gendered:
Trained only on real photos for the most part, so will perform poorly with illustrations, but is gendered, and can be used for male/female detection stack.
| Model | Target | mAP 50 | mAP 50-95 |Classes |Dataset size|Training Resolution|
| --------------------------- | --------------------- | ----------------------------- | ------------------------- |---------------|------------|-------------------|
| [Anzhcs ManFace v02 1024 y8n.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhcs%20ManFace%20v02%201024%20y8n.pt) | Face: real | 0.883(box),0.883(mask) | 0.778(box), 0.704(mask) |1(face) |~340 |1024|
| [Anzhcs WomanFace v05 1024 y8n.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhcs%20WomanFace%20v05%201024%20y8n.pt) | Face: real | 0.82(box),0.82(mask) | 0.713(box), 0.659(mask) |1(face) |~600 |1024|
Benchmark was performed in 640px.
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/W0vhyDYLaXuQnbA1Som8f.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/T5Q_mPJ8Ag6jfkaTpmNlM.png)
### Eyes segmentation:
Was trained for the purpose of inpainting eyes with Adetailer extension, and specializes on detecting anime eyes, particularly - sclera area, without adding eyelashes and outer eye area to detection.
Current benchmark is likely inaccurate (but it is all i have), due to data being re-scrambled multi times (dataset expansion for future versions).
| Model | Target | mAP 50 | mAP 50-95 |Classes |Dataset size|Training Resolution|
| --------------------------- | --------------------- | ----------------------------- | ------------------------- |---------------|------------|-------------------|
| [Anzhc Eyes -seg-hd.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20Eyes%20-seg-hd.pt) | Eyes: illustration | 0.925(box),0.868(mask) | 0.721(box), 0.511(mask) |1(eye) |~500(?) |1024|
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/o3zjKGjbXsx0NyB5PNJfM.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/WIPhP4STirM62b1qBUJWf.png)
### Head+Hair segmentation:
An old model (one of my first). Detects head + hair. Can be useful in likeness inpaint pipelines that need to be automated.
| Model | Target | mAP 50 | mAP 50-95 |Classes |Dataset size|Training Resolution|
| --------------------------- | --------------------- | ----------------------------- | ------------------------- |---------------|------------|-------------------|
| [Anzhc HeadHair seg y8n.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20HeadHair%20seg%20y8n.pt) | Head: illustration, real | 0.775(box),0.777(mask) | 0.576(box), 0.552(mask) |1(head) |~3180 |640|
| [Anzhc HeadHair seg y8m.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20HeadHair%20seg%20y8m.pt) | Head: illustration, real | 0.867(box),0.862(mask) | 0.674(box), 0.626(mask) |1(head) |~3180 |640|
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/Ic2n8gU4Kcod0XwQ9jzw8.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/oHm-Z5cOPsi7OfhmMEpZB.png)
### Breasts segmentation:
Model for segmenting breasts. Was trained on anime images only, therefore has very weak realistic performance, but still is possible.
| Model | Target | mAP 50 | mAP 50-95 |Classes |Dataset size|Training Resolution|
| --------------------------- | --------------------- | ----------------------------- | ------------------------- |---------------|------------|-------------------|
| [Anzhc Breasts Seg v1 1024n.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20Breasts%20Seg%20v1%201024n.pt) | Breasts: illustration | 0.742(box),0.73(mask) | 0.563(box), 0.535(mask) |1(breasts) |~2000 |1024|
| [Anzhc Breasts Seg v1 1024s.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20Breasts%20Seg%20v1%201024s.pt) | Breasts: illustration | 0.768(box),0.763(mask) | 0.596(box), 0.575(mask) |1(breasts) |~2000 |1024|
| [Anzhc Breasts Seg v1 1024m.pt](https://huggingface.co/Anzhc/Anzhcs_YOLOs/blob/main/Anzhc%20Breasts%20Seg%20v1%201024m.pt) | Breasts: illustration | 0.782(box),0.775(mask) | 0.644(box), 0.614(mask) |1(breasts) |~2000 |1024|
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/RoYVk1IgYH1ICiGQrMx6H.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/633b43d29fe04b13f46c8988/-QVv21yT6Z4r16M4RvFyS.png)
/--UNDER CONSTRUCTION--/