0dea0d6035a4623f46723379a9944ec50e4322ae,imgaug/augmenters/arithmetic.py,Add,__init__,#Add#Any#Any#Any#Any#Any#,96

Before Change

                 deterministic=False, random_state=None):
        super(Add, self).__init__(name=name, deterministic=deterministic, random_state=random_state)

        if ia.is_single_integer(value):
            ia.do_assert(-255 <= value <= 255, "Expected value to have range [-255, 255], got value %d." % (value,))
            self.value = Deterministic(value)
        elif ia.is_iterable(value):
            ia.do_assert(len(value) == 2, "Expected tuple/list with 2 entries, got %d entries." % (len(value),))
            self.value = DiscreteUniform(value[0], value[1])
        elif isinstance(value, StochasticParameter):
            self.value = value
        else:
            raise Exception("Expected float or int, tuple/list with 2 entries or StochasticParameter. Got %s." % (type(value),))

        if per_channel in [True, False, 0, 1, 0.0, 1.0]:
            self.per_channel = Deterministic(int(per_channel))
        elif ia.is_single_number(per_channel):
            ia.do_assert(0 <= per_channel <= 1.0, "Expected bool, or number in range [0, 1.0] for per_channel, got %s." % (type(per_channel),))
            self.per_channel = Binomial(per_channel)
        else:
            raise Exception("Expected per_channel to be boolean or number or StochasticParameter")

After Change

                 deterministic=False, random_state=None):
        super(Add, self).__init__(name=name, deterministic=deterministic, random_state=random_state)

        self.value = iap.handle_discrete_param(value, "value", value_range=(-255, 255), tuple_to_uniform=True, list_to_choice=True, allow_floats=False)
        self.per_channel = iap.handle_probability_param(per_channel, "per_channel")

    def _augment_images(self, images, random_state, parents, hooks):
        input_dtypes = meta.copy_dtypes_for_restore(images, force_list=True)

Instances