sccelik

import cv2
import os



#local binary patterns

from skimage.feature import local_binary_pattern
from matplotlib import pyplot

sccelik

import cv2
import os



#local binary patterns

from skimage.feature import local_binary_pattern
from matplotlib import pyplot

sccelik

import numpy as np
import cv2

# cv2.getGaborKernel(ksize, sigma, theta, lambda, gamma, psi, ktype)
# ksize - size of gabor filter (n, n)
# sigma - standard deviation of the gaussian function
# theta - orientation of the normal to the parallel stripes
# lambda - wavelength of the sunusoidal factor
# gamma - spatial aspect ratio
# psi - phase offset

sccelik

VGG-Face model for Keras

This is the Keras model of VGG-Face.

It has been obtained through the following method:

• vgg-face-keras:directly convert the vgg-face matconvnet model to keras model
• vgg-face-keras-fc:first convert vgg-face caffe model to mxnet model,and then convert it to keras model

Details about the network architecture can be found in the following paper: