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Add Segment Anything Model (SAM) #22654
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ArthurZucker
commented
Apr 11, 2023
sgugger
approved these changes
Apr 19, 2023
Merging as I need it to update the pipeline based on reviews. Will adresse remaining comments in a follow up PR |
ydshieh
pushed a commit
that referenced
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Apr 20, 2023
* 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>
novice03
pushed a commit
to novice03/transformers
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Jun 23, 2023
* 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>
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What does this PR do?
Original repo: https://github.com/facebookresearch/segment-anything
Segment Anything Model (SAM) is a recent model from Meta AI that makes it possible to predict image segmentation masks given an image and various inputs such as bounding boxes, 2D points or previous masks.
It is also mentioned in the original paper that the model can take textual input, but this feature has not been released yet in the original repository.
The release came with 3 weights, namely:
sam_vit_b
sam_vit_h
sam_vit_l
Their main difference is about the vision encoder size, the prompt encoder, and mask decoder should stay the same.
According to the paper, for each input, the model predicts 3 binary masks, corresponding to the region where the "object of interest" lives in the image.
cc @sgugger @amyeroberts