The default value for the `size` argument of `DepthProImageProcessor` is not synced with the documentation
Author: arjunaskykok
Pull request: no

At the the [`DepthProImageProcessor`](https://github.com/huggingface/transformers/blob/main/src/transformers/models/depth_pro/image_processing_depth_pro.py) class, the default value for the `size` argument is `None`, but the documentation says `{"height": 1536, "width": 1536}`, as can be seen in the following code:

```python
class DepthProImageProcessor(BaseImageProcessor):
    r"""
    Constructs a DepthPro image processor.

    Args:
        do_resize (`bool`, *optional*, defaults to `True`):
            Whether to resize the image's (height, width) dimensions to the specified `(size["height"],
            size["width"])`. Can be overridden by the `do_resize` parameter in the `preprocess` method.
        size (`dict`, *optional*, defaults to `{"height": 1536, "width": 1536}`):
            Size of the output image after resizing. Can be overridden by the `size` parameter in the `preprocess`
            method.
        resample (`PILImageResampling`, *optional*, defaults to `Resampling.BILINEAR`):
            Resampling filter to use if resizing the image. Can be overridden by the `resample` parameter in the
            `preprocess` method.
        do_rescale (`bool`, *optional*, defaults to `True`):
            Whether to rescale the image by the specified scale `rescale_factor`. Can be overridden by the `do_rescale`
            parameter in the `preprocess` method.
        rescale_factor (`int` or `float`, *optional*, defaults to `1/255`):
            Scale factor to use if rescaling the image. Can be overridden by the `rescale_factor` parameter in the
            `preprocess` method.
        do_normalize (`bool`, *optional*, defaults to `True`):
            Whether to normalize the image. Can be overridden by the `do_normalize` parameter in the `preprocess`
            method.
        image_mean (`float` or `List[float]`, *optional*, defaults to `IMAGENET_STANDARD_MEAN`):
            Mean to use if normalizing the image. This is a float or list of floats the length of the number of
            channels in the image. Can be overridden by the `image_mean` parameter in the `preprocess` method.
        image_std (`float` or `List[float]`, *optional*, defaults to `IMAGENET_STANDARD_STD`):
            Standard deviation to use if normalizing the image. This is a float or list of floats the length of the
            number of channels in the image. Can be overridden by the `image_std` parameter in the `preprocess` method.
    """

    model_input_names = ["pixel_values"]

    def __init__(
        self,
        do_resize: bool = True,
        size: Optional[Dict[str, int]] = None,
        resample: PILImageResampling = PILImageResampling.BILINEAR,
        do_rescale: bool = True,
        rescale_factor: Union[int, float] = 1 / 255,
        do_normalize: bool = True,
        image_mean: Optional[Union[float, List[float]]] = None,
        image_std: Optional[Union[float, List[float]]] = None,
        **kwargs,
    ):
```

Look at this:

```python
size (`dict`, *optional*, defaults to `{"height": 1536, "width": 1536}`):
            Size of the output image after resizing. Can be overridden by the `size` parameter in the `preprocess`
            method.
...
       size: Optional[Dict[str, int]] = None,
```

So, should we correct the default value for the `size` argument or fix the documentation?

cc: @qubvel 

Comments:
Hey @arjunaskykok, that's not a good practice to put mutable objects as defaults, so the default is resolved in the method itself

```python
size = size if size is not None else {"height": 1536, "width": 1536}
```

In the docs, we indicate the "real" default value, but it definitely can be improved by specifying that if `size` is left as `None`, it would be `{"height": 1536, "width": 1536}`

Fair.