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[Mask2Former] Add doc tests (#21232)

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* Add doc tests

* Add OneFormer resourcesé

* Fix merge

* Fix style

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
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NielsRogge
2023-01-25 12:34:43 +01:00
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parent 99e7905422
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4 changed files with 97 additions and 15 deletions
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docs/source/en/model_doc/mask2former.mdx
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@@ -25,6 +25,10 @@ Tips:
- Mask2Former uses the same preprocessing and postprocessing steps as [MaskFormer](maskformer). Use [`Mask2FormerImageProcessor`] or [`AutoImageProcessor`] to prepare images and optional targets for the model.
- To get the final segmentation, depending on the task, you can call [`~Mask2FormerImageProcessor.post_process_semantic_segmentation`] or [`~Mask2FormerImageProcessor.post_process_instance_segmentation`] or [`~Mask2FormerImageProcessor.post_process_panoptic_segmentation`]. All three tasks can be solved using [`Mask2FormerForUniversalSegmentation`] output, panoptic segmentation accepts an optional `label_ids_to_fuse` argument to fuse instances of the target object/s (e.g. sky) together.
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/mask2former_architecture.jpg" alt="drawing" width="600"/>
<small> Mask2Former architecture. Taken from the <a href="https://arxiv.org/abs/2112.01527">original paper.</a> </small>
This model was contributed by [Shivalika Singh](https://huggingface.co/shivi) and [Alara Dirik](https://huggingface.co/adirik). The original code can be found [here](https://github.com/facebookresearch/Mask2Former).
## Resources

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docs/source/en/model_doc/oneformer.mdx
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@@ -37,6 +37,15 @@ The figure below illustrates the architecture of OneFormer. Taken from the [orig
This model was contributed by [Jitesh Jain](https://huggingface.co/praeclarumjj3). The original code can be found [here](https://github.com/SHI-Labs/OneFormer).
## Resources
A list of official Hugging Face and community (indicated by 🌎) resources to help you get started with OneFormer.
- Demo notebooks regarding inference + fine-tuning on custom data can be found [here](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/OneFormer).
If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we will review it.
The resource should ideally demonstrate something new instead of duplicating an existing resource.
## OneFormer specific outputs
[[autodoc]] models.oneformer.modeling_oneformer.OneFormerModelOutput