Add Segment Anything Model (SAM) (#22654)

* initial commit

* keys match

* update, fix conversion

* fixes, inference working

* fix

* more fixes

* more fixes

* clean up

* more clean up

* fix copies and add convext copied layer norm

* stash

* pretty big upfate

* cleaning

* more cleaning

* fixup stuffs

* fix copies

* fix iinit

* update test removing tokenizer

* nits

* add pretrained

* more nits

* remove tracking of pipeline

* few fixes

* update san and conversion script

* fix mask decoder and prompt encoder conversion

* fixes

* small update

* fix order

* fix

* fix image embeddings

* nites

* few fixes

* fix logits

* clean up

* fixes boxes inference

* v1 AMG

* clean up

* some clean up

* multi points support

* amg working

* fixup

* clean up

* readme

* update toctree

* fix type hint

* multiple fixes

* fixup

* fixes

* updates

* updates

* more tests

* few fixes

* change to `SamForMaskGeneration`

* doc

* fixup

* fix more tests

* multiple fixes

* fix CI tests

* refactor processor

* renamings

* draft the pipeline

* refactor

* fix tests

* fix test

* few cleanings

* fix test

* edit pipelien support chunking

* udate

* add slow tests

* fix nit

* fixup

* fix nit

* current chunk pipleine

* cast boxes in fp32

* nit

* current updates

* piepleine works

* fixup

* clean up config

* fix slow tests

* fix slow tests

* clean up

* update doc and pipeline

* adds more slow tests

* fix slow tests

* cleaning

* tests pass

* add docstring

* fix copies

* clean up

* support batch of images

* style

* dummy is needed, add tests

* fix slow tests

* fix CI

* update

* adds more tests

* fixes

* fixes

* fixup

* fixes

* few fixes

* filter

* few fixes

* some refactor

* touches finales

* fix

* style

* remove pipeline files

* fixes nits

* revert pipeline changes

* fix test

* fixup

* remove automodel for automatic mask generation

* fix failing torch tests

* update mdx

* revert removal of `MODEL_FOR_AUTOMATIC_MASK_GENERATION_MAPPING`

* update sam config based on review

Co-authored-by: amyeroberts <aeroberts4444@gmail.com>
Co-authored-by: sgugger <sylvain.gugger@gmail.com>

* update low_resolution_masks -> pred_masks
inti ln with layer_norm_eps
add_decomposed_rel_pos doc
forward doc of SamForMaskGeneration

* update processor docstring

* remove image processor import empty

* update for testing

* output vision hidden states + clean recomm
also test all iou values

* fixup

* fixup

* remove unused

* Update src/transformers/models/sam/modeling_sam.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/sam/image_processing_sam.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* nits

* fix

* fix CI tests and slow tests

* replace with Amy's processor

* clearer docstring

* add `SamVisionNeck`

* refactor - all CI tests should pass

* fix broken import on Gcolab

* few fixes here and there

* fix another bug

* fix more bugs

* update and merge

* correct ckpt

* address comments

* add tips

* revert

* fix docstring

* replace with `SamModel`

* make fixup

* add support for bathed images and batch ed points

* make fixup this time, really

* make fixup again and again

* few fixes here and there, this should be the touche finale

* Update docs/source/en/model_doc/sam.mdx

* fixup

* correct checkpoints

* correct name

* rm unneeded file

* add notebook

---------

Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: amyeroberts <aeroberts4444@gmail.com>
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
This commit is contained in:
Arthur
2023-04-19 21:01:49 +02:00
committed by GitHub
parent 898efca72a
commit 474bf508df
30 changed files with 3645 additions and 1 deletions

View File

@@ -421,6 +421,7 @@ Current number of checkpoints: ![](https://img.shields.io/endpoint?url=https://h
1. **[RoCBert](https://huggingface.co/docs/transformers/model_doc/roc_bert)** (from WeChatAI) released with the paper [RoCBert: Robust Chinese Bert with Multimodal Contrastive Pretraining](https://aclanthology.org/2022.acl-long.65.pdf) by HuiSu, WeiweiShi, XiaoyuShen, XiaoZhou, TuoJi, JiaruiFang, JieZhou.
1. **[RoFormer](https://huggingface.co/docs/transformers/model_doc/roformer)** (from ZhuiyiTechnology), released together with the paper [RoFormer: Enhanced Transformer with Rotary Position Embedding](https://arxiv.org/abs/2104.09864) by Jianlin Su and Yu Lu and Shengfeng Pan and Bo Wen and Yunfeng Liu.
1. **[SegFormer](https://huggingface.co/docs/transformers/model_doc/segformer)** (from NVIDIA) released with the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo.
1. **[Segment Anything](https://huggingface.co/docs/transformers/main/model_doc/sam)** (from Meta AI) released with the paper [Segment Anything](https://ai.facebook.com/research/publications/segment-anything/) by Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alex Berg, Wan-Yen Lo, Piotr Dollar, Ross Girshick.
1. **[SEW](https://huggingface.co/docs/transformers/model_doc/sew)** (from ASAPP) released with the paper [Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition](https://arxiv.org/abs/2109.06870) by Felix Wu, Kwangyoun Kim, Jing Pan, Kyu Han, Kilian Q. Weinberger, Yoav Artzi.
1. **[SEW-D](https://huggingface.co/docs/transformers/model_doc/sew_d)** (from ASAPP) released with the paper [Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition](https://arxiv.org/abs/2109.06870) by Felix Wu, Kwangyoun Kim, Jing Pan, Kyu Han, Kilian Q. Weinberger, Yoav Artzi.
1. **[SpeechT5](https://huggingface.co/docs/transformers/model_doc/speecht5)** (from Microsoft Research) released with the paper [SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing](https://arxiv.org/abs/2110.07205) by Junyi Ao, Rui Wang, Long Zhou, Chengyi Wang, Shuo Ren, Yu Wu, Shujie Liu, Tom Ko, Qing Li, Yu Zhang, Zhihua Wei, Yao Qian, Jinyu Li, Furu Wei.