Better design for RandomSizedBBoxSafeCrop without implicit resizing

This is current definition of RandomSizedBBoxSafeCrop class, which is on the transforms.py

class RandomSizedBBoxSafeCrop(DualTransform):
    """Crop a random part of the input and rescale it to some size without loss of bboxes.

    Args:
        height (int): height after crop and resize.
        width (int): width after crop and resize.
        erosion_rate (float): erosion rate applied on input image height before crop.
        interpolation (OpenCV flag): flag that is used to specify the interpolation algorithm. Should be one of:
            cv2.INTER_NEAREST, cv2.INTER_LINEAR, cv2.INTER_CUBIC, cv2.INTER_AREA, cv2.INTER_LANCZOS4.
            Default: cv2.INTER_LINEAR.
        p (float): probability of applying the transform. Default: 1.

    Targets:
        image, mask, bboxes

    Image types:
        uint8, float32
    """

    def __init__(self, height, width, erosion_rate=0.0, interpolation=cv2.INTER_LINEAR, always_apply=False, p=1.0):
        super(RandomSizedBBoxSafeCrop, self).__init__(always_apply, p)
        self.height = height
        self.width = width
        self.interpolation = interpolation
        self.erosion_rate = erosion_rate

    def apply(self, img, crop_height=0, crop_width=0, h_start=0, w_start=0, interpolation=cv2.INTER_LINEAR, **params):
        crop = F.random_crop(img, crop_height, crop_width, h_start, w_start)
        return F.resize(crop, self.height, self.width, interpolation)

And this is my customization on the same class, without implicit resizing.

class RandomSizedBBoxSafeCrop(DualTransform):
    """Crop a random part of the input and rescale it to some size without loss of bboxes.

    Args:
        erosion_rate (float): erosion rate applied on input image height before crop.
        p (float): probability of applying the transform. Default: 1.

    Targets:
        image, mask, bboxes

    Image types:
        uint8, float32
    """

    def __init__(self, erosion_rate=0.0, always_apply=False, p=1.0):
        super(RandomSizedBBoxSafeCrop, self).__init__(always_apply, p)
        self.erosion_rate = erosion_rate

    def apply(self, img, crop_height=0, crop_width=0, h_start=0, w_start=0, **params):
        return F.random_crop(img, crop_height, crop_width, h_start, w_start)

I think the latter is better design, since it has simpler code and fits into more general use cases. If the resizing feature is really need for someone, it can be done explicitly by composing this with Resize.

[Dipet]

Also we can set height and width to None by default . And if one of them is None do not use resize

[Dipet]

Implemented in #579