gabor_final.py

import scipy as sp
from scipy import arange, sqrt, array, amax, ceil, io, fliplr, flipud
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import ipdb
import time
from tqdm import tqdm


# rot = np.array([90,-67.5,-45,-22.5,0,45,67.5])
# RF_siz = sp.arange(33,67,2)
# Div = sp.arange(4,3.15,-.05)

rot = np.array([90,-67.5,-45,-22.5,0,22.5,45,67.5])
RF_siz = sp.arange(33,67,2)
Div = sp.arange(4,3.15,-.05)

def create_gabor(rot,RF_siz,Div,plot,num=10):
    count = 0
    numFilterSizes   = len(RF_siz)
    numSimpleFilters = len(rot)
    lamb = (RF_siz * 2.)/Div
    sigma  = lamb * 0.8
    G      = 0.3
    phases = [0, np.pi/2]

    # Initialize Filterbank
    alt_fb = np.zeros((65,65,1,272),dtype=np.float32)


    # for k in tqdm(range(0,numFilterSizes-1)):
    for k in tqdm(range(1,numFilterSizes+1)):
        for r in tqdm(range(1,numSimpleFilters+1)):

            f = np.zeros([RF_siz[numFilterSizes-1],RF_siz[numFilterSizes-1]])
            fx = np.zeros([RF_siz[numFilterSizes-1],RF_siz[numFilterSizes-1]])

            ## Parameters
            theta     = rot[r-1]*(np.pi/180)
            filtSize  = RF_siz[k-1]

            img_center = ceil(33.0) ## New center for padding with zeros

            center    = ceil(filtSize/2.0) ## Old and possibly more accurate center

            filtSizeL = center-1
            filtSizeR = filtSize-filtSizeL-1
            sigmaq    = (sigma[k-1]) * (sigma[k-1])


            # Compute filter values
            for iPhi in range(1,3):
                for i in range(int(-1 * filtSizeL),int(filtSizeR+1)):
                    for j in range(int(-1 * filtSizeL),int(filtSizeR+1)):

                        if (sqrt((i**2)+(j**2))>(filtSize/2 )) :
                            E = 0
                        else :
                            x = i*np.cos(theta) - j*np.sin(theta)
                            y = i*np.sin(theta) + j*np.cos(theta)

                            E = np.exp((-1*((x**2)+ (G**2) * (y**2)))/(2*sigmaq))*np.cos(2*np.pi*x/lamb[k-1] + phases[iPhi-1])

                        f[int(j+img_center-1),int(i+img_center-1)] = E


                ## Append to fb (filterbank)
                f = f - np.mean(np.mean(f))
                f = f / sqrt(np.sum(np.sum(f**2)))

                # Reshaped image
                alt_fb[:,:,0,count] = f
                count += 1

                if (plot):
                    if count % num == 0:
                        plt.imshow(f,cmap='Greys')
                        plt.show()

    return (np.array(alt_fb))






## Test Plotting ----------------------
#create_gabor(rot,RF_siz,Div)

## Create Dictionary ---------------
gabor_array = create_gabor(rot,RF_siz,Div,False)
bias = np.zeros([272])
gabor_dictionary = {}
gabor_dictionary['gabors'] = gabor_array,bias

f,x = gabor_dictionary['gabors']


## Save Dictionary ----------------------
np.save('/Users/charlieholtz/Desktop/gabors/gabor_dictionary.npy', gabor_dictionary)

## Test Dictionary
#weights = tf.get_variable('weights', shape = [filter_height, filter_width, input_channels/groups, num_filters])



## Load Dictionary From Save File ----------------------
# b = np.load('/Users/charlieholtz/Desktop/hermann/Gabor Filters/gabor_dictionary.npy').item()
# f,x = b['gabors']
# print(f.shape)