text: Title: [Detections] extend `from_transformers` with segmentation models support
  Body: ### Description
  
  Currently, Supervision only supports Transformers object detection models. Let's expand [`from_transformers`](https://github.com/roboflow/supervision/blob/781a064d8aa46e3875378ab6aba1dfdad8bc636c/supervision/detection/core.py#L391) by adding support for segmentation models.
  
  ### API
  
  The code below should enable the annotation of an image with segmentation results.
  
  ```python
  import torch
  import supervision as sv
  from PIL import Image
  from transformers import DetrImageProcessor, DetrForSegmentation
  
  processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
  model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
  
  image = Image.open(<PATH TO IMAGE>)
  inputs = processor(images=image, return_tensors="pt")
  
  with torch.no_grad():
      outputs = model(**inputs)
  
  width, height = image.size
  target_size = torch.tensor([[height, width]])
  results = processor. post_process_segmentation(
      outputs=outputs, target_sizes=target_size)[0]
  detections = sv.Detections.from_transformers(results)
  
  mask_annotator = sv.MaskAnnotator()
  
  annotated_image = mask.annotate(scene=image, detections=detections)
  ```
  
  ### Additional
  
  - [Transformers DETR Docs](https://huggingface.co/docs/transformers/en/model_doc/detr)
  - Note: Please share a Google Colab with minimal code to test the new feature. We know it's additional work, but it will speed up the review process. The reviewer must test each change. Setting up a local environment to do this is time-consuming. Please ensure that Google Colab can be accessed without any issues (make it public). Thank you! 🙏🏻 