[WIP] Add OneformerFastImageProcessor (#38343)

* [WIP] OneformerFastImageProcessor

* update init

* Fully working oneformer image processor fast

* change Nearest to Neares exact interpolation where needed

* fix doc

---------

Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
This commit is contained in:
space_samurai
2025-07-23 02:11:39 +05:30
committed by GitHub
parent 4884b6bf41
commit c6d0500d15
11 changed files with 1224 additions and 128 deletions

View File

@@ -38,7 +38,7 @@ This model was contributed by [Jitesh Jain](https://huggingface.co/praeclarumjj3
## Usage tips
- OneFormer requires two inputs during inference: *image* and *task token*.
- OneFormer requires two inputs during inference: *image* and *task token*.
- During training, OneFormer only uses panoptic annotations.
- If you want to train the model in a distributed environment across multiple nodes, then one should update the
`get_num_masks` function inside in the `OneFormerLoss` class of `modeling_oneformer.py`. When training on multiple nodes, this should be
@@ -69,7 +69,14 @@ The resource should ideally demonstrate something new instead of duplicating an
[[autodoc]] OneFormerImageProcessor
- preprocess
- encode_inputs
- post_process_semantic_segmentation
- post_process_instance_segmentation
- post_process_panoptic_segmentation
## OneFormerImageProcessorFast
[[autodoc]] OneFormerImageProcessorFast
- preprocess
- post_process_semantic_segmentation
- post_process_instance_segmentation
- post_process_panoptic_segmentation
@@ -87,4 +94,3 @@ The resource should ideally demonstrate something new instead of duplicating an
[[autodoc]] OneFormerForUniversalSegmentation
- forward