Gabor Filters for CNN in Tensorflow, python

Question

I want to use Gabor filters as a kernel in CNN, but I can't find a solution. Something I find but doesn't work.

import tensorflow as tf
import cv2
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Input, Dense, Conv2D, MaxPooling2D, UpSampling2D, BatchNormalization
from tensorflow.keras.layers import Activation, Flatten, Dropout, Conv2DTranspose, LeakyReLU, Concatenate, Lambda

from tensorflow.keras import backend as K

def get_gabor_tensor(ksize, sigmas, thetas, lambdas, gammas, psis):
    n_kernels = len(sigmas) * len(thetas) * len(lambdas) * len(gammas) * len(psis)
    gabors = []
    for sigma in sigmas:
        for theta in thetas:
            for lambd in lambdas:
                for gamma in gammas:
                    for psi in psis:
                        params = {'ksize': ksize, 'sigma': sigma,
                                  'theta': theta, 'lambd': lambd,
                                  'gamma': gamma, 'psi': psi}
                        gf = cv2.getGaborKernel(**params, ktype=cv2.CV_32F)
                        gf = K.expand_dims(gf, -1)
                        gabors.append(gf)
    assert len(gabors) == n_kernels
    print(f"Created {n_kernels} kernels.")
    return K.stack(gabors, axis=-1)


def convolve_tensor(x, kernel_tensor=None):
    return K.conv2d(x, kernel_tensor, padding='same')


def gabor_layer(layer, n_filters=16, kernel_size=3):
    ksize=(3, 3)
    sigmas = [1, 2, 3, 4]
    thetas = np.linspace(0, np.pi, 4, endpoint=False)
    lambdas=[8, 16, 32, 64]
    psis = np.linspace(0, 2*np.pi, 2, endpoint=False)
    gammas = np.linspace(1, 0, 2, endpoint=False)

    tensor = get_gabor_tensor(ksize, sigmas, thetas, lambdas, gammas, psis)

    x = Lambda(convolve_tensor, arguments={'kernel_tensor': tensor})(layer)
    c1 = Conv2D(filters=16, kernel_size=(3, 3), padding='same')(layer)
    p1 = MaxPooling2D((2, 2))(c1)
    output = Dropout(0.1)(p1)
    return output

And error

ValueError: Depth of output (256) is not a multiple of the number of groups (3) for 'lambda/convolution' (op: 'Conv2D') with input shapes: [?,96,96,3], [3,3,1,256].

The solution is from https://github.com/bdevans/GaborNet/blob/master/gabornet.py

Answer 1

Pass the Input(shape=(128,192,1)) ; i.e with Gray image. I got the same error and it got solved.