Merge branch 'master' of https://github.com/mohitwildbeast/Facial-Recognition-Using-One-Shot-Learning-Siamese-Network

Author: msindev

README.md

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+# Facial-Recognition-Using-FaceNet-Siamese-One-Shot-Learning
+This program is used to implement Facial Recognition using Siamese Network architecture. The implementation of the project is based on the research paper : 
+
+> FaceNet: A Unified Embedding for Face Recognition and Clustering
+> [arXiv:1503.03832](https://arxiv.org/abs/1503.03832) by [Florian Schroff](https://arxiv.org/search/cs?searchtype=author&query=Schroff%2C+F), [Dmitry Kalenichenko](https://arxiv.org/search/cs?searchtype=author&query=Kalenichenko%2C+D), [James Philbin](https://arxiv.org/search/cs?searchtype=author&query=Philbin%2C+J)
+
+Facenet implements concept of Triplet Loss function to minimize the distance between anchor and positive images, and increase the distance between anchor and negative images.
+
+### Prerequisites
+
+    h5py==2.8.0
+	Keras==2.2.4
+	tensorflow==1.13.0rc2
+	dlib==19.16.0
+	opencv_python==3.4.3.18
+	imutils==0.5.1
+	numpy==1.15.2
+	matplotlib==3.0.0
+	scipy==1.1.0
+
+Install the packages using `pip install -r requirements.txt`
+
+### Usage
+To use the facial recognition system, you need to have a database of images through which the model will calculate image embeddings and show the output. 
+The images which are in the database are stored as .jpg files in the directory `./images`.
+
+
+To generate your own dataset and add more faces to the system, use the following procedure:
+
+> Sit in front of your webcam.
+> Use the Image_Dataset_Generator.py script to save 50 images of your face.
+> Use this command: `python Image_Dataset_Generator.py` to generate images which will be saved in images folder.
+
+To use the facial recognition system, run the command : 
+`python face_recognizer.py` 
+
+### References
+
+ 1. The code has been implemented using deeplearning.ai course Convolutional Networks Week 4 Assignment, which has the files `fr_utils.py` and `inception_blocks_v2.py`
+ 2. The keras implementation of the model is by Victor Sy Wang's implementation and was loaded using his code:  [https://github.com/iwantooxxoox/Keras-OpenFace](https://github.com/iwantooxxoox/Keras-OpenFace).