def build(self, input_shape):
theta = np.array(range(self.K)) / self.K * np.pi
self.contrast_gb = GaborFilters(self.ksize,
theta=theta,
octave=self.use_octave)
self.contrast_BU = BotUpSaliency(self.ksize,
K=self.K,
steps=self.n_steps,
epsilon=self.epsilon)
# img = np.zeros((256, 256, 3))
# img[:128, :128, 0] = 255
# img[128:, 128:, 1] = 255
# plt.imshow(img)
# ----------------- build model ---------------
# build model
input = Input(shape=(256, 256, 3))
# -------------------- Gabor 1 ------------------ #
conf = config['Gabor'][0]
n_rot = conf['n_rot']
thetas = np.array(range(n_rot)) / n_rot * np.pi
gabor_layer1 = GaborFilters((15, 15),
theta=thetas,
sigma=conf['sigmas'],
lamda=np.array(conf['lamdas']) * np.pi,
gamma=conf['gamma'],
per_channel=False)
x1 = gabor_layer1(input)
# -------------------- Gabor 2 ------------------ #
conf = config['Gabor'][1]
n_rot = conf['n_rot']
thetas = np.array(range(n_rot)) / n_rot * np.pi
gabor_layer2 = GaborFilters((15, 15),
theta=thetas,
sigma=conf['sigmas'],
lamda=np.array(conf['lamdas']) * np.pi,
gamma=conf['gamma'],
per_channel=False)
x2 = gabor_layer2(input)
# img = np.zeros((256, 256, 3))
# img[:128, :128, 0] = 255
# img[128:, 128:, 1] = 255
# plt.imshow(img)
# build model
input = Input(shape=(256, 256, 3))
n_rot = 8
thetas = np.array(range(n_rot)) / n_rot * np.pi
sigmas = config['sigmas']
lamdas = np.array(config['lamdas']) * np.pi
gamma = config['gamma']
gabor_layer = GaborFilters((15, 15),
theta=thetas,
sigma=sigmas,
lamda=lamdas,
gamma=gamma,
per_channel=False)
x = gabor_layer(input)
# print("shape gabor_kernel", np.shape(gabor_layer.kernel))
# g_kernels = np.moveaxis(gabor_layer.kernel, -1, 0)
# for gb in g_kernels:
# if np.shape(gb)[-1] == 1:
# gb = np.squeeze(gb)
# gb = (gb+1)/2
# plt.figure()
# plt.imshow(gb.astype(np.float32))
# plt.show()
model = Model(inputs=input, outputs=x)
# build model
input = Input(shape=(256, 256, 3))
n_rot = config['n_rot']
thetas = np.array(range(n_rot)) / n_rot * np.pi
lamdas = np.array(config['lamdas']) * np.pi
gamma = config['gamma']
phi = np.array(config['phi']) * np.pi
use_octave = config['use_octave']
octave = config['octave']
gabor_layer = GaborFilters((15, 15),
theta=thetas,
lamda=lamdas,
gamma=gamma,
phi=phi,
use_octave=use_octave,
octave=octave,
per_channel=False,
per_color_channel=True)
x = gabor_layer(input)
# print("shape gabor_kernel", np.shape(gabor_layer.kernel))
g_kernels = np.moveaxis(gabor_layer.kernel, -1, 0)
# for gb in g_kernels:
# if np.shape(gb)[-1] == 1:
# gb = np.squeeze(gb)
# gb = (gb+1)/2
# plt.figure()
# plt.imshow(gb.astype(np.float32))
# plt.show()