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@ -67,14 +67,14 @@ df = DeepFace.find(img_path = "img1.jpg", db_path = "C:/workspace/my_db", model_
FaceNet, VGG-Face, ArcFace and Dlib are [overperforming](https://youtu.be/i_MOwvhbLdI) ones based on experiments. You can find the scores of those models on both [Labeled Faces in the Wild](https://sefiks.com/2020/08/27/labeled-faces-in-the-wild-for-face-recognition/) and YouTube Faces in the Wild data sets declared by its creators. FaceNet, VGG-Face, ArcFace and Dlib are [overperforming](https://youtu.be/i_MOwvhbLdI) ones based on experiments. You can find the scores of those models on both [Labeled Faces in the Wild](https://sefiks.com/2020/08/27/labeled-faces-in-the-wild-for-face-recognition/) and YouTube Faces in the Wild data sets declared by its creators.
| Model | LFW Score | YFW Score | | Model | LFW Score | YTF Score |
| --- | --- | --- | | --- | --- | --- |
| Facenet512 | 99.65% | - | | Facenet512 | 99.65% | - |
| ArcFace | 99.41% | - | | ArcFace | 99.41% | - |
| Dlib | 99.38 % | - | | Dlib | 99.38 % | - |
| Facenet | 99.20% | - | | Facenet | 99.20% | - |
| VGG-Face | 98.78% | 97.40% | | VGG-Face | 98.78% | 97.40% |
| Human-beings | 97.53% | - | | *Human-beings* | 97.53% | - |
| OpenFace | 93.80% | - | | OpenFace | 93.80% | - |
| DeepID | - | 97.05% | | DeepID | - | 97.05% |