Add: doc page for the object detection task
This is a PR for the [#20805](https://github.com/huggingface/transformers/issues/20805) issue. The guide has content and working code examples for:
*  Introduction
*  Loading CPPE-5 dataset from Hub
*  Preprocessing both images and annotations. Images are augmented, and annotations are reformatted to be in the format DETR expects
*  Training with Trainer
*  Evaluation
*  Inference
This PR replaces the https://github.com/huggingface/transformers/pull/20874 <|||||>To preserve the discussion, here's @sayakpaul 's comment relevant to the CI issue: https://github.com/huggingface/transformers/pull/20874#issuecomment-1366717321<|||||>_The documentation is not available anymore as the PR was closed or merged._<|||||>> * Make sure to split long code samples in several smaller ones with text introducing each step. The evaluation in particular is too long and may be too technical for this guide.

I agree that the evaluation part is a bit too technical, but unfortunately at the moment, there's no simpler way (hopefully soon there will be an easier way to have coco evaluation metrics). But I can certainly split it up somewhat. 
<|||||>Thank you for the feedback @sayakpaul !
 > Do you have a Colab Notebook where this code has been tested (preferably with outputs)?

Yes, I do. Here's my playground notebook with outputs. All the code examples are working. The only issue is that I didn't really pay too much attention to the hyperparameters, so the resulting model isn't very good. It would probably improve with more epochs and better learning rate decay. But I ran out of free GPU in Colab today :D
https://colab.research.google.com/drive/1wPTZJajGRhhh00Lnz7-8E5qE1x_qL1Of#scrollTo=5w2lsRRYPXDN


<|||||>@NielsRogge note that finetune/fine-tune has no decided standard in the doc/transformers and both are used equally.