Face-Recognition-using-FaceNet-master.zip

# Face-Recognition-using-FaceNet This face recognition system is implemented upon a pre-trained FaceNet model achieving a state-of-the-art accuracy. The system comes with both Live recognition & Image recognition. It is trained on faces of some celebrities. For any queries Contact: [Ankur Goswami](https://github.com/Ankur1401/) * __Installing dependencies:__ * For Anaconda users: `conda install --file requirements.txt`<br> * For python users: `pip install -r requirements.txt`<br> (even Anaconda users can use this if they use anaconda prompt instead of terminal) * __Downloading the model__:<br> The repository requires an additional file to work. The file is too large to upload here. So I've provided a Google Drive link of it. Download the file and keep it inside [`/data/model/`](https://github.com/Ankur1401/Face-Recognition-using-FaceNet/tree/master/data/model) directory.<br> [Click Here](https://drive.google.com/open?id=1PZ_6Zsy1Vb0s0JmjEmVd8FS99zoMCiN1) to download the file. * __Training on other faces:__ <br> To train model on different faces, follow the given steps:<br> 1. Put the images containing clear frontal face in [`/data/images/`](https://github.com/Ankur1401/Face-Recognition-using-FaceNet/tree/master/data/images) directory. 1. Open the repository directory in terminal and run following commands in given order: 1. `cd script` 1. `python generate_data.py` 1. Follow program instructions. * __Testing/Detecting faces:__ <br> 1. __Face Recognition from Images__: 1. Put the images containing the faces to predict in [`/test/`](https://github.com/Ankur1401/Face-Recognition-using-FaceNet/tree/master/test) directory. 1. Open the repository directory in terminal and run following command: ``` python image_recognition.py ``` 1. Output images will then be available in [`/test/predicted/`](https://github.com/Ankur1401/Face-Recognition-using-FaceNet/tree/master/test/predicted) directory. 1. __Live Face Recognition(Obviously using camera):__ <br>Open the repository directory in terminal and run following command: ``` python live_recognition.py ``` ## Examples: __NOTE:__ Faces with __Unidentified__ labels are faces on which the model is not trained. __Example #1:__ <br>Before:<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/vampire-diaries.jpg width=50%> <br>After:<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/predicted/vampire-diaries.jpg width=50%> __Example #2:__ <br>Before:<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/the-avengers-walt03.jpg width=50%> <br>After:<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/predicted/the-avengers-walt03.jpg width=50%> __Example #3:__ <br>Before:<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/2ec945ecd5f7c08789f3ef5da5287410.jpg width=50%> <br>After:<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/predicted/2ec945ecd5f7c08789f3ef5da5287410.jpg width=50%> __Example #4:__ <br>Before:<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/3840x2160-avengers-cast-photocall-moscow-05.JPG width=75%> <br>After:(Need to zoom)<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/predicted/3840x2160-avengers-cast-photocall-moscow-05.JPG width=75%> __Example #5:__ <br>In this example, the model was trained on faces of my friends. <br>Before:<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/00000PORTRAIT_00000_BURST20180310144236486.jpg width=75%> <br>After:<br> <img src=https://github.com/Ankur1401/Face-Recognition-using-FaceNet/blob/master/test/predicted/00000PORTRAIT_00000_BURST20180310144236486.jpg width=75%>