Repository: huggingface/transformers
Pull request: Fix: siglip image processor rgb_convert is not being applied correctly.

# What does this PR do?

```python
        # All transformations expect numpy arrays.
        images = [to_numpy_array(image) for image in images]

        if do_convert_rgb:
            images = [convert_to_rgb(image) for image in images]
```
The convert_to_rgb function is not being applied because ndarray values are being input 
(convert_to_rgb simply returns the input value if it's not a PIL.Image).

If an image with RGBA or similar format is input, the conversion doesn't work properly, 
causing the following error in the infer_channel_dimension_format method:

```python
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/transformers/image_utils.py", line 254, in infer_channel_dimension_format
    raise ValueError("Unable to infer channel dimension format")
ValueError: Unable to infer channel dimension format
```

`transformers` version: 4.46.0.dev0


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

@amyeroberts

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Changed files:
filename: src/transformers/models/siglip/image_processing_siglip.py
patch: @@ -198,12 +198,12 @@ def preprocess(
             size=size,
             resample=resample,
         )
-        # All transformations expect numpy arrays.
-        images = [to_numpy_array(image) for image in images]
-
         if do_convert_rgb:
             images = [convert_to_rgb(image) for image in images]
 
+        # All transformations expect numpy arrays.
+        images = [to_numpy_array(image) for image in images]
+
         if is_scaled_image(images[0]) and do_rescale:
             logger.warning_once(
                 "It looks like you are trying to rescale already rescaled images. If the input"