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Face Recognition with Machine Learning

Project description

This Package used for Face Recognition with Machine Algorithm

It's implemented with face encodings

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

  1. KNN - K-Nearest Neighbors
  2. LOG_REG_BIN - Logistic Regression with two classes
  3. LOG_REG_MUL - Logistic Regression with more than two classes
  4. 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)

Project details


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