def __init__(self, k1=0.01, k2=0.03, kernel_size=3, max_value=1.0):
self.__name__ = 'DSSIMObjective'
self.kernel_size = kernel_size
self.k1 = k1
self.k2 = k2
self.max_value = max_value
self.c1 = (self.k1 * self.max_value)**2
self.c2 = (self.k2 * self.max_value)**2
self.dim_ordering = K.image_data_format()
self.backend = KC.backend()
def __init__(self, k1=0.01, k2=0.03, kernel_size=3, max_value=1.0):
"""
Difference of Structural Similarity (DSSIM loss function). Clipped between 0 and 0.5
Note : You should add a regularization term like a l2 loss in addition to this one.
# Arguments
k1: Parameter of the SSIM (default 0.01)
k2: Parameter of the SSIM (default 0.03)
kernel_size: Size of the sliding window (default 3)
max_value: Max value of the output (default 1.0)
"""
self.__name__ = 'DSSIMObjective'
self.kernel_size = kernel_size
self.k1 = k1
self.k2 = k2
self.max_value = max_value
self.c1 = (self.k1 * self.max_value)**2
self.c2 = (self.k2 * self.max_value)**2
self.dim_ordering = K.image_dim_ordering()
self.backend = KC.backend()
def int_shape(x):
return KC.int_shape(x) if KC.backend() == 'tensorflow' else KC.shape(x)
