Method change_input_dim

yolox/data/dataloading.py:123–161

This function will compute a new size and update it on the next mini_batch. Args: multiple (int or tuple, optional): values to multiply the randomly generated range by. Default **32** random_range (tuple, optional): This (min, max) tuple sets the rang

(self, multiple=32, random_range=(10, 19))

        self.batch_sampler.mosaic = False

    def change_input_dim(self, multiple=32, random_range=(10, 19)):
        """This function will compute a new size and update it on the next mini_batch.

        Args:
            multiple (int or tuple, optional): values to multiply the randomly generated range by.
                Default **32**
            random_range (tuple, optional): This (min, max) tuple sets the range
                for the randomisation; Default **(10, 19)**

        Return:
            tuple: width, height tuple with new dimension

        Note:
            The new size is generated as follows: |br|
            First we compute a random integer inside ``[random_range]``.
            We then multiply that number with the ``multiple`` argument,
            which gives our final new input size. |br|
            If ``multiple`` is an integer we generate a square size. If you give a tuple
            of **(width, height)**, the size is computed
            as :math:`rng * multiple[0], rng * multiple[1]`.

        Note:
            You can set the ``random_range`` argument to **None** to set
            an exact size of multiply. |br|
            See the example above for how this works.
        """
        if random_range is None:
            size = 1
        else:
            size = random.randint(*random_range)

        if isinstance(multiple, int):
            size = (size * multiple, size * multiple)
        else:
            size = (size * multiple[0], size * multiple[1])

        self.batch_sampler.new_input_dim = size

        return size


def list_collate(batch):