OneFormerProcessor、MaskFormerImageProcessor will cause errors if segmentation_maps only have elements 0 and 1
Author: yuyijiong
Pull request: no

### System Info

transformers-4.26.0  do not have this bug
but transformers-4.27.0.dev0 has.

### Who can help?

_No response_

### Information

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

### Tasks

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

### Reproduction

```python
from transformers import OneFormerProcessor, OneFormerForUniversalSegmentation, OneFormerImageProcessor, OneFormerConfig
from transformers import Mask2FormerImageProcessor, Mask2FormerForUniversalSegmentation
from PIL import Image
import requests
import torch
import numpy as np
import matplotlib

processor = OneFormerProcessor.from_pretrained("shi-labs/oneformer_ade20k_swin_tiny",num_text=134,do_reduce_labels=True,)

image_np=np.random.randint(0,255,(3,512,512))

#segmentation_maps only have elements 0 and 1
segmentation_maps = torch.randint(0, 2, (image_np.shape[1], image_np.shape[2]), dtype=torch.long)

inst2class={1: 4}

raw_inputs=processor.image_processor([image_np],
                   task_inputs=["panoptic"],
                   segmentation_maps=[segmentation_maps],
                   return_tensors="pt",
                   instance_id_to_semantic_id=inst2class,
                   do_reduce_labels=True,
                   ignore_index=None)

```
#ERROR
```
E:\condaenv\yaogan\lib\site-packages\transformers\models\oneformer\image_processing_oneformer.py:419: FutureWarning: The `reduce_labels` argument is deprecated and will be removed in v4.27. Please use `do_reduce_labels` instead.
  warnings.warn(
Traceback (most recent call last):
  File "E:\condaenv\yaogan\lib\site-packages\IPython\core\interactiveshell.py", line 3460, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-2-ed9733992fe8>", line 23, in <module>
    raw_inputs=processor.image_processor([image_np],
  File "E:\condaenv\yaogan\lib\site-packages\transformers\models\oneformer\image_processing_oneformer.py", line 524, in __call__
    return self.preprocess(images, task_inputs=task_inputs, segmentation_maps=segmentation_maps, **kwargs)
  File "E:\condaenv\yaogan\lib\site-packages\transformers\models\oneformer\image_processing_oneformer.py", line 708, in preprocess
    encoded_inputs = self.encode_inputs(
  File "E:\condaenv\yaogan\lib\site-packages\transformers\models\oneformer\image_processing_oneformer.py", line 962, in encode_inputs
    masks, classes = self.convert_segmentation_map_to_binary_masks(
  File "E:\condaenv\yaogan\lib\site-packages\transformers\models\oneformer\image_processing_oneformer.py", line 516, in convert_segmentation_map_to_binary_masks
    return convert_segmentation_map_to_binary_masks(
  File "E:\condaenv\yaogan\lib\site-packages\transformers\models\oneformer\image_processing_oneformer.py", line 288, in convert_segmentation_map_to_binary_masks
    class_id = instance_id_to_semantic_id[label + 1 if reduce_labels else label]
KeyError: 255
```
This bug is caused by a **resize** function of OneFormerProcessor, which convert segmentation_maps to PIL.Image and then convert to np.ndarray. After **resize**, segmentation_maps have elements 0 and 255, so the bug arise. 

### Expected behavior

fix this bug before release 4.27.0 as stable version
transformers-4.26.0  do not have this bug

Comments:
cc @amyeroberts @alaradirik