From 8ae7784256062fbaef411c926c1abfac9873b08d Mon Sep 17 00:00:00 2001
From: Alara Dirik <8944735+alaradirik@users.noreply.github.com>
Date: Tue, 2 Aug 2022 18:43:58 +0300
Subject: [PATCH] update maskformer docs (#18423)

* update maskformer docs

* fix typo
---
 docs/source/en/model_doc/maskformer.mdx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/source/en/model_doc/maskformer.mdx b/docs/source/en/model_doc/maskformer.mdx
index 886b0a587c..b06ed2cd56 100644
--- a/docs/source/en/model_doc/maskformer.mdx
+++ b/docs/source/en/model_doc/maskformer.mdx
@@ -33,7 +33,7 @@ Tips:
   `get_num_masks` function inside in the `MaskFormerLoss` class of `modeling_maskformer.py`. When training on multiple nodes, this should be
   set to the average number of target masks across all nodes, as can be seen in the original implementation [here](https://github.com/facebookresearch/MaskFormer/blob/da3e60d85fdeedcb31476b5edd7d328826ce56cc/mask_former/modeling/criterion.py#L169).
 - One can use [`MaskFormerFeatureExtractor`] to prepare images for the model and optional targets for the model.
-- To get the final segmentation, depending on the task, you can call [`~MaskFormerFeatureExtractor.post_process_semantic_segmentation`] or [`~MaskFormerFeatureExtractor.post_process_panoptic_segmentation`]. Both tasks can be solved using [`MaskFormerForInstanceSegmentation`] output, the latter needs an additional `is_thing_map` to know which instances must be merged together..
+- To get the final segmentation, depending on the task, you can call [`~MaskFormerFeatureExtractor.post_process_semantic_segmentation`] or [`~MaskFormerFeatureExtractor.post_process_panoptic_segmentation`]. Both tasks can be solved using [`MaskFormerForInstanceSegmentation`] output, panoptic segmentation accepts an optional `label_ids_to_fuse` argument to fuse instances of the target object/s (e.g. sky) together.
 
 The figure below illustrates the architecture of MaskFormer. Taken from the [original paper](https://arxiv.org/abs/2107.06278).