Face Recognition with Machine Learning and Face Clustering
Project description
This Package used for Face Recognition with Machine Algorithm
Installing Steps for requirements python package
Installing dlib on Ubuntu
The following instructions were gathered on Ubuntu 16.04 but should work on newer versions of Ubuntu as well.
To get started, let’s install our required dependencies:
sudo apt-get update
sudo apt-get install build-essential cmake
sudo apt-get install libopenblas-dev liblapack-dev
sudo apt-get install libx11-dev libgtk-3-dev
sudo apt-get install python python-dev python-pip
sudo apt-get install python3 python3-dev python3-pip
after
pip install dlib
Installing pyfacy models on Ubuntu
pip install pyfacy_dlib_models
Installing imutils on Ubuntu
pip install imutils
Installing numpy, scipy and sklearn
pip install numpy
pip install scipy
pip install scikit-learn
Examples:
Read Image
from pyfacy import utils
img = utils.load_image('<image src>')
ex:
img = utils.load_image('manivannan.jpg')
Face Encodings:
from pyfacy import utils
img = utils.load_image('<image src>')
encodings = utils.img_to_encodings(img)
Compare Two faces
from pyfacy import utils
image1 = utils.load_image('<image1 src>')
image2 = utils.load_image('<image2 src>')
matching,distance = utils.compare_faces(image1,image2)
Note: The compare_faces return Boolean and Distance between two faces
Example for Face Recognition using ML
Implementing Algorithms
- KNN - K-Nearest Neighbors
- LOG_REG_BIN - Logistic Regression with two classes
- LOG_REG_MUL - Logistic Regression with more than two classes
- LDA - Linear Discriminant Analysis
Training , Save model and Predict Image
from pyfacy import face_recog
from pyfacy import utils
mdl = face_recog.Face_Recog_Algorithm()
# Train the Model
# Implemented only four algorithms above mentioned and put the shortform
mdl.train('pyfacy/Test_DS',alg='LOG_REG_MUL')
# Save the Model
mdl.save_model()
# Predicting Image
img = utils.load_image('<image src>')
mdl.predict(img)
Loading model and Predict Image
from pyfacy import face_recog
from pyfacy import utils
mdl = face_recog.Face_Recog_Algorithm()
# Load Model
mdl.load_model('model.pkl')
# Predicting Image
img = utils.load_image('<image src>')
mdl.predict(img)
Face Clustering
Cluster the image_src
from pyfacy import face_clust
# Create object for Cluster class with your source path(only contains jpg images)
mdl = face_clust.Face_Clust_Algorithm('./pyfacy/cluster')
# Load the faces to the algorithm
mdl.load_faces()
# Save the group of images to custom location(if the arg is empty store to current location)
mdl.save_faces('./pyfacy')
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