VaeImageProcessorLDM3D.preprocess fails for batched NumPy RGB/depth inputs

## Describe the bug

`VaeImageProcessorLDM3D.preprocess` documents that NumPy RGB and depth inputs can be either a single image or a batch. A single 3D RGB/depth pair works, but a valid 4D batch raises `ValueError: axes don't match array`.

The RGB batch is concatenated and converted to a PyTorch tensor before the depth batching condition is evaluated. The condition then checks `rgb[0].ndim` instead of the original `depth[0].ndim`, so the 4D depth batch is stacked into a 5D array and passed to `numpy_to_pt`, which expects four axes.

Relevant source: https://github.com/huggingface/diffusers/blob/d6726f38a0c5ca6c06a8f227fb7bade3486ed98d/src/diffusers/image_processor.py#L1217

I would like to contribute the focused one-line correction and a regression test once a maintainer confirms the scope, following the repository's AI-assisted contribution policy.

## Reproduction

```python
import numpy as np

from diffusers import VaeImageProcessorLDM3D

processor = VaeImageProcessorLDM3D(vae_scale_factor=1)
rgb = np.zeros((2, 8, 8, 3), dtype=np.float32)
depth = np.zeros((2, 8, 8, 1), dtype=np.float32)

processed_rgb, processed_depth = processor.preprocess(rgb, depth)
print(processed_rgb.shape, processed_depth.shape)
```

Expected shapes:

```text
torch.Size([2, 3, 8, 8]) torch.Size([2, 1, 8, 8])
```

Actual result:

```text
ValueError: axes don't match array
```

The same reproduction fails on both Diffusers 0.39.0 and current `main` at `d6726f38`. Passing corresponding single-image arrays with shapes `(8, 8, 3)` and `(8, 8, 1)` succeeds.

## Logs

```text
Traceback (most recent call last):
...
File "diffusers/image_processor.py", line 1218, in preprocess
depth = self.numpy_to_pt(depth)
File "diffusers/image_processor.py", line 188, in numpy_to_pt
images = torch.from_numpy(images.transpose(0, 3, 1, 2))
ValueError: axes don't match array
```

## System Info

- Diffusers version: 0.39.0; also reproduced on 0.40.0.dev0 at `d6726f38`
- Platform: Windows-10-10.0.26200-SP0
- Python version: 3.10.11
- PyTorch version: 2.13.0+cpu
- huggingface_hub version: 1.27.0
- Safetensors version: 0.8.0
- GPU used in script: No
- Distributed or parallel setup: No

## Who can help?

@sayakpaul @DN6

AI disclosure: I used Codex to help identify and reproduce the behavior, verify it on the latest release and current main, search existing issues and PRs, and draft this report. I reviewed the reproduction and diagnosis and will personally handle any follow-up.

Beginne in src/diffusers/image_processor.py bei VaeImageProcessorLDM3D.preprocess ungefähr in Zeile 1217 und untersuche anschließend numpy_to_pt ungefähr in Zeile 188. Führe die bereitgestellte Reproduktion für gebatchte RGB-/Tiefendaten aus und füge Regressionstests für die erwarteten Tensorformen hinzu. Erledigt ist die Aufgabe, wenn gültige 4D-Eingaben nicht mehr den Achsenfehler auslösen und der Fall mit einem einzelnen Bild weiterhin funktioniert.

Vom Indexierungsmodell aus dem Issue-Text verfasst.