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README.md

@@ -1,10 +1,16 @@
-# Face Recognition using OpenCV
- - Create dataset of face images
- - - Detect faces using ```deploy.prototxt``` and ```res10_300x300_ssd_iter_140000.caffemodel```. (Learn more about [face detection](https://github.com/aakashjhawar/face-detection))
- - Extract face embeddings for each face present in the image using pretrained [OpenFace](https://cmusatyalab.github.io/openface/) model ```openface_nn4.small2.v1.t7```. 
- - Train a SVM model on the face embeddings to recognize faces 
+# Face recognition module
+
+**Forked from [aakashjhawar/face-recognition-using-deep-learning](https://github.com/aakashjhawar/face-recognition-using-deep-learning)**
+
+*The following content is copied from aakashjhawar/face-recognition-using-deep-learning*
+
+- Create dataset of face images
+- - Detect faces using ``deploy.prototxt`` and ``res10_300x300_ssd_iter_140000.caffemodel``. (Learn more about [face detection](https://github.com/aakashjhawar/face-detection))
+- Extract face embeddings for each face present in the image using pretrained [OpenFace](https://cmusatyalab.github.io/openface/) model ``openface_nn4.small2.v1.t7``.
+- Train a SVM model on the face embeddings to recognize faces
 
 ## Overview of OpenFace for a single input image
+
 1. Detect faces with a pre-trained models from dlib or OpenCV.
 2. Transform the face for the neural network. This repository uses dlib's real-time pose estimation with OpenCV's affine transformation to try to make the eyes and bottom lip appear in the same location on each image.
 3. Use a deep neural network to represent (or embed) the face on a 128-dimensional unit hypersphere. The embedding is a generic representation for anybody's face. Unlike other face representations, this embedding has the nice property that a larger distance between two face embeddings means that the faces are likely not of the same person. This property makes clustering, similarity detection, and classification tasks easier than other face recognition techniques where the Euclidean distance between features is not meaningful.
@@ -14,31 +20,45 @@
 ![Working of OpenCV Face detector](https://github.com/aakashjhawar/face-recognition-using-opencv/blob/master/images/openface.jpg)
 
 ## Getting Started
+
 How to use
-```    
+
+```
 git clone https://github.com/aakashjhawar/face-recognition-using-opencv
 cd face-recognition-using-opencv
 ```
- - Create dataset of face images.
- - Place the face images in dataset folder.
- - Extract facial embeddings.
-```python extract_embeddings.py```
- - Train the SVM model
-```python train_model.py```
- - Test the model
-```python recognize_video.py```
+
+- Create dataset of face images.
+- Place the face images in dataset folder.
+- Extract facial embeddings.
+  ``python extract_embeddings.py``
+- Train the SVM model
+  ``python train_model.py``
+- Test the model
+  ``python recognize_video.py``
 
 ## Prerequisites
 
 - Python 3.5
 - OpenCV
+
 ```
 sudo apt-get install python-opencv
 ```
 
-## Results 
+## Results
 
 #### Detect and recognize faces from video camera-
+
 ![Result](https://github.com/aakashjhawar/face-recognition-using-opencv/blob/master/images/output1.png)
 
 
+## Changelog of this fork :
+
+
+- Added a method to create a directory for the user.
+- Added a method to implement the dataset for face recognition.
+- Added a progress bar to the method to implement the dataset.
+- Added a method to train the model.
+- Added a method to recognize the face.
+- Added a method to extract the face.