Image Segmentation Guide missing dependencies/imports and overwritten variables
Author: evanwong1020
Pull request: no

### System Info

- `transformers` version: 4.38.1     
- Platform: Windows-10-10.0.19045-SP0
- Python version: 3.11.4
- Huggingface_hub version: 0.20.3    
- Safetensors version: 0.4.2
- Accelerate version: 0.27.2
- Accelerate config: not found
- PyTorch version (GPU?): 2.2.1+cu121 (True)
- Tensorflow version (GPU?): 2.15.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No

### Who can help?

I have not tested the TensorFlow version, only the PyTorch version.

So far, I have identified:
- Missing pip install accelerate
- Missing imports:
  - torch
  - torch.nn as nn
  - numpy as np
- `train_ds[0]` will not display the image, you need to access the ['image'] within the dictionary structure.
  - `ds[0]["image"]` will run into an error. ds was overridden and will require you to call `ds['test'][0]["image"]` if you're looking for the test set, and `ds['train'][0]["image"]` if you wanted the training set.
- `train_transforms` and `val_transforms` convert the ds images into pixel values. When trying to access `image = ds[0]["image"]` later on, it throws a KeyError since the images have been converted already.
- `ade_palette()` is not defined. It's in the TensorFlow models library in a file called [get_dataset_colormap](https://github.com/tensorflow/models/blob/master/research/deeplab/utils/get_dataset_colormap.py), but I was unable to import it.
- The trainer class requires an extra two parameters `tokenizer` and `data_collator` to generate the preprocesing_config.json file.
```python
trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=train_ds,
    eval_dataset=test_ds,
    tokenizer=image_processor,
    data_collator=default_data_collator,
    compute_metrics=compute_metrics,
)
```
  - This should be fixed with the PR linked on this [issue](https://github.com/huggingface/transformers/issues/29790) I posted earlier

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

1. Follow along the Image Segmentation guide at https://huggingface.co/docs/transformers/tasks/semantic_segmentation
2. Upon reaching the cell that reads `train_ds[0]`, the output will be
```python
{'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=300x240>,
 'annotation': <PIL.PngImagePlugin.PngImageFile image mode=L size=300x240>,
 'scene_category': 1001}
```
3. Upon reaching the cell that begins with `training_args = TrainingArguments(`, you will receive an import error: 
```python
`ImportError: Using the `Trainer` with `PyTorch` requires `accelerate>=0.21.0`: Please run `pip install transformers[torch]` or `pip install accelerate -U`
```
4. Under the inference section that reads `image = ds[0]["image"]`, you will receive a KeyError due to ds being overwritten earlier, and the `train_transforms` and `val_transforms` functions converting the images to pixel values.
5. The very last cell attempts to call the `ade_palette()` function, which is not defined.

### Expected behavior

Upon reaching the cell that reads `train_ds[0]`, the output should be a viewable image. Fixable by changing to `train_ds[0]['image']`

Upon reaching the cell that begins with `training_args = TrainingArguments(`, the model should start its training process without issue. Should be resolved by the issue and PR mentioned earlier.

Calling `image = ds[0]["image"]` should display an image. I think it's easier to just reload the dataset, since converting the pixel values back into an image would take a lot of work.

The `ade_palette()` function should be imported properly or defined at some point. I'm not sure if this is an issue for everyone else, but I can't seem to import it via TensorFlow.

Comments:
cc @stevhliu and @merveenoyan