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yolo/README.md

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+---
+license: apache-2.0
+library_name: ultralytics
+datasets:
+- wider_face
+- skytnt/anime-segmentation
+tags:
+- pytorch
+---
+
+# YOLOv8 Detection Model
+from
+```
+Bingsu/adetailer
+```
+## Datasets
+
+### Face
+
+- [Anime Face CreateML](https://universe.roboflow.com/my-workspace-mph8o/anime-face-createml)
+- [xml2txt](https://universe.roboflow.com/0oooooo0/xml2txt-njqx1)
+- [AN](https://universe.roboflow.com/sed-b8vkf/an-lfg5i)
+- [wider face](http://shuoyang1213.me/WIDERFACE/index.html)
+
+### Hand
+
+- [AnHDet](https://universe.roboflow.com/1-yshhi/anhdet)
+- [hand-detection-fuao9](https://universe.roboflow.com/catwithawand/hand-detection-fuao9)
+
+### Person
+
+- [coco2017](https://cocodataset.org/#home) (only person)
+- [AniSeg](https://github.com/jerryli27/AniSeg)
+- [skytnt/anime-segmentation](https://huggingface.co/datasets/skytnt/anime-segmentation)
+
+### deepfashion2
+
+- [deepfashion2](https://github.com/switchablenorms/DeepFashion2)
+
+| id  | label                 |
+| --- | --------------------- |
+| 0   | short_sleeved_shirt   |
+| 1   | long_sleeved_shirt    |
+| 2   | short_sleeved_outwear |
+| 3   | long_sleeved_outwear  |
+| 4   | vest                  |
+| 5   | sling                 |
+| 6   | shorts                |
+| 7   | trousers              |
+| 8   | skirt                 |
+| 9   | short_sleeved_dress   |
+| 10  | long_sleeved_dress    |
+| 11  | vest_dress            |
+| 12  | sling_dress           |
+
+## Info
+
+| Model                       | Target                | mAP 50                        | mAP 50-95                     |
+| --------------------------- | --------------------- | ----------------------------- | ----------------------------- |
+| face_yolov8n.pt             | 2D / realistic face   | 0.660                         | 0.366                         |
+| face_yolov8n_v2.pt          | 2D / realistic face   | 0.669                         | 0.372                         |
+| face_yolov8s.pt             | 2D / realistic face   | 0.713                         | 0.404                         |
+| face_yolov8m.pt             | 2D / realistic face   | 0.737                         | 0.424                         |
+| face_yolov9c.pt             | 2D / realistic face   | 0.748                         | 0.433                         |
+| hand_yolov8n.pt             | 2D / realistic hand   | 0.767                         | 0.505                         |
+| hand_yolov8s.pt             | 2D / realistic hand   | 0.794                         | 0.527                         |
+| hand_yolov9c.pt             | 2D / realistic hand   | 0.810                         | 0.550                         |
+| person_yolov8n-seg.pt       | 2D / realistic person | 0.782 (bbox)<br/>0.761 (mask) | 0.555 (bbox)<br/>0.460 (mask) |
+| person_yolov8s-seg.pt       | 2D / realistic person | 0.824 (bbox)<br/>0.809 (mask) | 0.605 (bbox)<br/>0.508 (mask) |
+| person_yolov8m-seg.pt       | 2D / realistic person | 0.849 (bbox)<br/>0.831 (mask) | 0.636 (bbox)<br/>0.533 (mask) |
+| deepfashion2_yolov8s-seg.pt | realistic clothes     | 0.849 (bbox)<br/>0.840 (mask) | 0.763 (bbox)<br/>0.675 (mask) |
+
+## Usage
+
+```python
+from huggingface_hub import hf_hub_download
+from ultralytics import YOLO
+
+path = hf_hub_download("Bingsu/adetailer", "face_yolov8n.pt")
+model = YOLO(path)
+```
+
+```python
+import cv2
+from PIL import Image
+
+img = "https://farm5.staticflickr.com/4139/4887614566_6b57ec4422_z.jpg"
+output = model(img)
+pred = output[0].plot()
+pred = cv2.cvtColor(pred, cv2.COLOR_BGR2RGB)
+pred = Image.fromarray(pred)
+pred
+```
+
+![image](https://i.imgur.com/9ny1wmD.png)
+
+
+## Unsafe files
+
+![image](https://i.imgur.com/9Btuy8j.png)
+
+Since `getattr` is classified as a dangerous pickle function, any segmentation model that uses it is classified as unsafe.
+
+All models were created and saved using the official [ultralytics](https://github.com/ultralytics/ultralytics) library, so it's okay to use files downloaded from a trusted source.
+
+See also: https://huggingface.co/docs/hub/security-pickle

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