Bug: RuntimeError: max() in ObjectCentricSSI._compute_scale_and_shift when mask is empty

_Sorry I am a student working on research regarding this tool, and don't have time atm to fix this into a tested pull request, but figured it would be helpful to point out since the problem seems to be arising with the min() function as well._

When processing an image where the valid mask area becomes completely empty (e.g., an off-center object that gets cropped out, or an empty mask being passed in), the pipeline crashes with a RuntimeError during the pointmap normalization step.

In sam3d_objects/data/dataset/tdfy/img_and_mask_transforms.py, inside the ObjectCentricSSI._compute_scale_and_shift method, the code filters pointmap_flat using the mask. If no valid points are found, mask_points becomes an empty tensor.

Calling .max() on an empty tensor in PyTorch without a specified dimension throws an error, causing the script to crash before it can reach the intended ValueError or fallback logging.

````
File "sam-3d-objects/sam3d_objects/data/dataset/tdfy/img_and_mask_transforms.py", line 597, in normalize
_scale, _shift = self._compute_scale_and_shift(pointmap, mask)
File "sam-3d-objects/sam3d_objects/data/dataset/tdfy/img_and_mask_transforms.py", line 550, in _compute_scale_and_shift
if mask_points.isfinite().max() == 0:
RuntimeError: max(): Expected reduction dim to be specified for input.numel() == 0. Specify the reduction dim with the 'dim' argument.
````

**Steps to Reproduce:**

- Pass an image and a completely black mask (all zeros) through the preprocessing pipeline using the ObjectCentricSSI normalizer.
- The mask_points tensor evaluates to size [3, 0].
- The check if `mask_points.isfinite().max() == 0:` throws the RuntimeError.

**Suggested Fix:**
Adding a quick numel() == 0 check before .max() safely catches the empty mask and allows the intended fallback logic to execute. This allowed my instance of the model to run as expected.

File: sam3d_objects/data/dataset/tdfy/img_and_mask_transforms.py
Line ~550:

`if mask_points.numel() == 0 or mask_points.isfinite().max() == 0:`