From 51545d69e8080e1b74a0f630aeabef71e80f06a8 Mon Sep 17 00:00:00 2001 From: Niels Rogge Date: Thu, 10 Nov 2022 09:06:36 +0000 Subject: [PATCH] Update README.md --- README.md | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index fd36ed0..4bd7003 100644 --- a/README.md +++ b/README.md @@ -9,19 +9,19 @@ datasets: # MaskFormer -MaskFormer model trained on ade-20k. It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresearch/MaskFormer/blob/da3e60d85fdeedcb31476b5edd7d328826ce56cc/mask_former/modeling/criterion.py#L169). +MaskFormer model trained on ADE20k semantic segmentation. It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresearch/MaskFormer/blob/da3e60d85fdeedcb31476b5edd7d328826ce56cc/mask_former/modeling/criterion.py#L169). -Disclaimer: The team releasing Mask did not write a model card for this model so this model card has been written by the Hugging Face team. +Disclaimer: The team releasing MaskFormer did not write a model card for this model so this model card has been written by the Hugging Face team. ## Model description -MaskFormer addresses semantic segmentation with a mask classification paradigm instead. +MaskFormer addresses instance, semantic and panoptic segmentation with the same paradigm: by predicting a set of masks and corresponding labels. Hence, all 3 tasks are treated as if they were instance segmentation. ![model image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/maskformer_architecture.png) ## Intended uses & limitations -You can use the raw model for image classification. See the [model hub](https://huggingface.co/models?search=maskformer) to look for +You can use this particular checkpoint for semantic segmentation. See the [model hub](https://huggingface.co/models?search=maskformer) to look for other fine-tuned versions on a task that interests you. ### How to use @@ -46,9 +46,7 @@ Here is how to use this model: >>> masks_queries_logits = outputs.masks_queries_logits >>> # you can pass them to feature_extractor for postprocessing ->>> output = feature_extractor.post_process_segmentation(outputs) >>> output = feature_extractor.post_process_semantic_segmentation(outputs) ->>> output = feature_extractor.post_process_panoptic_segmentation(outputs) ``` For more code examples, we refer to the [documentation](https://huggingface.co/docs/transformers/master/en/model_doc/maskformer). \ No newline at end of file