---
license: agpl-3.0
tags:
- pytorch
- YOLOv8
- art
- Ultralytics
base_model:
- Ultralytics/YOLOv8
library_name: ultralytics
pipeline_tag: object-detection
---
## 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             | Face: illustration, real   | LOST DATA               | LOST DATA             |2(male, female)|LOST DATA| 640|
  | Anzhc Face -seg-hd.pt          | Face: illustration, real   | LOST DATA               | LOST DATA             |2(male, female)|LOST DATA|1024|
  | Anzhc Face seg 640 v2 y8n.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   | 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 | 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  | 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     | Face: real   | 0.883(box),0.883(mask)        | 0.778(box), 0.704(mask)   |1(face)        |~340        |1024|
  | Anzhcs WomanFace v05 1024 y8n.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 segmnetation:
PLACEHOLDER

| Model                       | Target                | mAP 50                        | mAP 50-95                 |Classes        |Dataset size|Training Resolution|
| --------------------------- | --------------------- | ----------------------------- | ------------------------- |---------------|------------|-------------------|
  | Anzhcs ManFace v02 1024 y8n.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   | Face: real   | 0.82(box),0.82(mask)          | 0.713(box), 0.659(mask)   |1(face)        |~600        |1024|

### Head+Hair segmentation:
PLACEHOLDER

| Model                       | Target                | mAP 50                        | mAP 50-95                 |Classes        |Dataset size|Training Resolution|
| --------------------------- | --------------------- | ----------------------------- | ------------------------- |---------------|------------|-------------------|
  | Anzhcs ManFace v02 1024 y8n.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   | Face: real   | 0.82(box),0.82(mask)          | 0.713(box), 0.659(mask)   |1(face)        |~600        |1024|

### 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   | Breasts: illustration   | 0.742(box),0.73(mask)        | 0.563(box), 0.535(mask)   |1(breasts)        |~2000        |1024|
  | Anzhc Breasts Seg v1 1024s.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   | 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--/