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@ -194,7 +194,7 @@ Age model got ± 4.65 MAE; gender model got 97.44% accuracy, 96.29% precision an
**Face Detectors** - [`Demo`](https://youtu.be/GZ2p2hj2H5k)
Face detection and alignment are important early stages of a modern face recognition pipeline. Experiments show that just alignment increases the face recognition accuracy almost 1%. [`OpenCV`](https://sefiks.com/2020/02/23/face-alignment-for-face-recognition-in-python-within-opencv/), [`SSD`](https://sefiks.com/2020/08/25/deep-face-detection-with-opencv-in-python/), [`Dlib`](https://sefiks.com/2020/07/11/face-recognition-with-dlib-in-python/), [`MTCNN`](https://sefiks.com/2020/09/09/deep-face-detection-with-mtcnn-in-python/), [`Faster MTCNN`](https://github.com/timesler/facenet-pytorch), [`RetinaFace`](https://sefiks.com/2021/04/27/deep-face-detection-with-retinaface-in-python/), [`MediaPipe`](https://sefiks.com/2022/01/14/deep-face-detection-with-mediapipe/), [`YOLOv8 Face`](https://github.com/derronqi/yolov8-face), [`YuNet`](https://github.com/ShiqiYu/libfacedetection) and [`CenterFace`](https://github.com/Star-Clouds/CenterFace) detectors are wrapped in deepface.
Face detection and alignment are important early stages of a modern face recognition pipeline. Experiments show that just alignment increases the face recognition accuracy almost 1%. [`OpenCV`](https://sefiks.com/2020/02/23/face-alignment-for-face-recognition-in-python-within-opencv/), [`Ssd`](https://sefiks.com/2020/08/25/deep-face-detection-with-opencv-in-python/), [`Dlib`](https://sefiks.com/2020/07/11/face-recognition-with-dlib-in-python/), [`MtCnn`](https://sefiks.com/2020/09/09/deep-face-detection-with-mtcnn-in-python/), `Faster MTCNN`, [`RetinaFace`](https://sefiks.com/2021/04/27/deep-face-detection-with-retinaface-in-python/), [`MediaPipe`](https://sefiks.com/2022/01/14/deep-face-detection-with-mediapipe/), `Yolo`, `YuNet` and `CenterFace` detectors are wrapped in deepface.
<p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/master/icon/detector-portfolio-v6.jpg" width="95%" height="95%"></p>
@ -318,9 +318,7 @@ You can also run these commands if you are running deepface with docker. Please
## FAQ and Troubleshooting
If you believe you have identified a bug or encountered a limitation in DeepFace that is not covered in the [existing issues](https://github.com/serengil/deepface/issues) or [closed issues](https://github.com/serengil/deepface/issues?q=is%3Aissue+is%3Aclosed), kindly open a new issue. Ensure that your submission includes clear and detailed reproduction steps, such as your Python version, your DeepFace version (provided by `DeepFace.__version__`), versions of dependent packages (provided by pip freeze), specifics of any exception messages, details about how you are calling DeepFace, and the input image(s) you are using.
Additionally, it is possible to encounter issues due to recently released dependencies, primarily Python itself or TensorFlow. It is recommended to synchronize your dependencies with the versions [specified in my environment](https://github.com/serengil/deepface/blob/master/requirements_local) and [same python version](https://github.com/serengil/deepface/blob/master/Dockerfile#L2) not to have potential compatibility issues.
If you believe you have identified a bug or encountered a limitation in DeepFace that is not covered in the [existing issues](https://github.com/serengil/deepface/issues) or [closed issues](https://github.com/serengil/deepface/issues?q=is%3Aissue+is%3Aclosed), kindly open a new issue. Ensure that your submission includes clear and detailed reproduction steps, such as your Python version, your DeepFace version, versions of dependent packages (provided by pip freeze), specifics of any exception messages, details about how you are calling DeepFace, and the input image(s) you are using.
## Contribution
@ -352,7 +350,7 @@ If you use deepface in your research for facial recogntion purposes, please cite
pages = {23-27},
year = {2020},
doi = {10.1109/ASYU50717.2020.9259802},
url = {https://doi.org/10.1109/ASYU50717.2020.9259802},
url = {https://ieeexplore.ieee.org/document/9259802},
organization = {IEEE}
}
```
@ -367,7 +365,7 @@ If you use deepface in your research for facial attribute analysis purposes such
pages = {1-4},
year = {2021},
doi = {10.1109/ICEET53442.2021.9659697},
url = {https://doi.org/10.1109/ICEET53442.2021.9659697},
url = {https://ieeexplore.ieee.org/document/9659697},
organization = {IEEE}
}
```
@ -378,6 +376,10 @@ Also, if you use deepface in your GitHub projects, please add `deepface` in the
DeepFace is licensed under the MIT License - see [`LICENSE`](https://github.com/serengil/deepface/blob/master/LICENSE) for more details.
DeepFace wraps some external face recognition models: [VGG-Face](http://www.robots.ox.ac.uk/~vgg/software/vgg_face/), [Facenet](https://github.com/davidsandberg/facenet/blob/master/LICENSE.md), [OpenFace](https://github.com/iwantooxxoox/Keras-OpenFace/blob/master/LICENSE), [DeepFace](https://github.com/swghosh/DeepFace), [DeepID](https://github.com/Ruoyiran/DeepID/blob/master/LICENSE.md), [ArcFace](https://github.com/leondgarse/Keras_insightface/blob/master/LICENSE), [Dlib](https://github.com/davisking/dlib/blob/master/dlib/LICENSE.txt), [SFace](https://github.com/opencv/opencv_zoo/blob/master/models/face_recognition_sface/LICENSE) and [GhostFaceNet](https://github.com/HamadYA/GhostFaceNets/blob/main/LICENSE). Besides, age, gender and race / ethnicity models were trained on the backbone of VGG-Face with transfer learning. Licence types will be inherited if you are going to use those models. Please check the license types of those models for production purposes.
DeepFace wraps some external face recognition models: [VGG-Face](http://www.robots.ox.ac.uk/~vgg/software/vgg_face/), [Facenet](https://github.com/davidsandberg/facenet/blob/master/LICENSE.md), [OpenFace](https://github.com/iwantooxxoox/Keras-OpenFace/blob/master/LICENSE), [DeepFace](https://github.com/swghosh/DeepFace), [DeepID](https://github.com/Ruoyiran/DeepID/blob/master/LICENSE.md), [ArcFace](https://github.com/leondgarse/Keras_insightface/blob/master/LICENSE), [Dlib](https://github.com/davisking/dlib/blob/master/dlib/LICENSE.txt), [SFace](https://github.com/opencv/opencv_zoo/blob/master/models/face_recognition_sface/LICENSE) and [GhostFaceNet](https://github.com/HamadYA/GhostFaceNets/blob/main/LICENSE). Besides, age, gender and race / ethnicity models were trained on the backbone of VGG-Face with transfer learning.
Similarly, DeepFace wraps many face detectors: [OpenCv](https://github.com/opencv/opencv/blob/4.x/LICENSE), [Ssd](https://github.com/opencv/opencv/blob/master/LICENSE), [Dlib](https://github.com/davisking/dlib/blob/master/LICENSE.txt), [MtCnn](https://github.com/ipazc/mtcnn/blob/master/LICENSE), [Fast MtCnn](https://github.com/timesler/facenet-pytorch/blob/master/LICENSE.md), [RetinaFace](https://github.com/serengil/retinaface/blob/master/LICENSE), [MediaPipe](https://github.com/google/mediapipe/blob/master/LICENSE), [YuNet](https://github.com/ShiqiYu/libfacedetection/blob/master/LICENSE), [Yolo](https://github.com/derronqi/yolov8-face/blob/main/LICENSE) and [CenterFace](https://github.com/Star-Clouds/CenterFace/blob/master/LICENSE).
Licence types will be inherited if you are going to use those models. Please check the license types of those models for production purposes.
DeepFace [logo](https://thenounproject.com/term/face-recognition/2965879/) is created by [Adrien Coquet](https://thenounproject.com/coquet_adrien/) and it is licensed under [Creative Commons: By Attribution 3.0 License](https://creativecommons.org/licenses/by/3.0/).